IA-QA — 130+ QA & Dev Tools for AI Agents

{'type': 'object', 'required': ['variant_a', 'variant_b'], 'properties': {'variant_a': {'type': 'object', 'properties': {'name': {'type': 'string', 'description': 'Name/label for variant A'}, 'scores': {'type': 'array', 'items': {'type': 'number'}, 'description': 'Array of scores (0-100)'}}, 'description': 'First variant configuration with name and score array'}, 'variant_b': {'type': 'object', 'properties': {'name': {'type': 'string', 'description': 'Name/label for variant B'}, 'scores': {'type': 'array', 'items': {'type': 'number'}, 'description': 'Array of scores (0-100)'}}, 'description': 'Second variant configuration with name and score array'}}}

{'type': 'object', 'properties': {'max': {}, 'min': {}, 'mean': {'type': 'string'}, 'count': {'type': 'number'}, 'median': {'type': 'string'}, 'winner': {}, 'std_dev': {'type': 'string'}, 'variant_a': {'type': 'object'}, 'variant_b': {'type': 'object'}, 'recommendation': {'type': 'number'}, 'improvement_percent': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['version2'], 'properties': {'context': {'type': 'string', 'description': 'Optional PR title or feature context for better analysis'}, 'version1': {'type': 'string', 'description': 'Original code (before changes). If omitted, only the new version is analysed.'}, 'version2': {'type': 'string', 'description': 'New/modified code (after changes)'}}}

{'type': 'object', 'properties': {'bugs': {'type': 'array', 'items': {'type': 'object'}}, 'disclaimer': {'type': 'string'}, 'notAnalysed': {'type': 'array', 'items': {'type': 'string'}}, 'overallRisk': {'type': 'string'}, 'rulesApplied': {'type': 'number'}, 'scannedLines': {'type': 'number'}, 'totalSuggestions': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['responses'], 'properties': {'reference': {'type': 'string', 'description': 'Optional ground-truth answer. If set, each output is also ranked by closeness to it and the closest one is named.'}, 'responses': {'type': 'array', 'items': {'type': 'object', 'required': ['text'], 'properties': {'text': {'type': 'string', 'description': 'The produced output'}, 'label': {'type': 'string', 'description': 'Human name for this candidate (e.g. model id)'}}}, 'minItems': 2, 'description': 'The outputs to analyze (same task, N models/prompts/versions). Each item is a plain string or { "label": "GPT-4o", "text": "..." }. At least 2 required.'}}}

{'type': 'object', 'properties': {'count': {}, 'summary': {'type': 'string'}, 'consensus': {}, 'reference_ranking': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'Base64 string to decode'}}}

{'type': 'object', 'properties': {'decoded': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'Text to encode'}}}

{'type': 'object', 'properties': {'encoded': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['responses'], 'properties': {'responses': {'type': 'array', 'items': {'type': 'object', 'required': ['variantId', 'answer'], 'properties': {'answer': {'type': 'string', 'description': 'The LLM response text for this variant'}, 'variantId': {'type': 'string', 'description': 'Identifier for the demographic variant (e.g. "male", "female", "western", "young")'}}}, 'minItems': 2, 'description': 'Array of variant responses to compare for bias'}}}

{'type': 'object', 'properties': {'verdict': {'type': 'string'}, 'lengthCV': {'type': 'number'}, 'biasScore': {'type': 'number'}, 'sentiments': {'type': 'array', 'items': {'type': 'object', 'properties': {'ratio': {'type': 'number'}, 'negative': {'type': 'number'}, 'positive': {'type': 'number'}, 'variantId': {'type': 'string'}}}}, 'avgSimilarity': {'type': 'number'}, 'minSimilarity': {'type': 'number'}, 'sentimentVariance': {'type': 'number'}, 'pairwiseSimilarities': {'type': 'array', 'items': {'type': 'object', 'properties': {'a': {'type': 'string'}, 'b': {'type': 'string'}, 'score': {'type': 'number'}}}}}, 'additionalProperties': True}

{'type': 'object', 'required': ['query', 'documents'], 'properties': {'b': {'type': 'number', 'description': 'Length normalization factor (default: 0.75)'}, 'k1': {'type': 'number', 'description': 'Term frequency saturation (default: 1.5)'}, 'query': {'type': 'string', 'description': 'The search query'}, 'top_k': {'type': 'number', 'description': 'Return top K results (default: all)'}, 'documents': {'type': 'array', 'items': {'type': 'string'}, 'description': 'Array of documents to rank'}}}

{'type': 'object', 'properties': {'b': {}, 'k1': {}, 'index': {}, 'query': {}, 'results': {}, 'bm25_score': {'type': 'number'}, 'doc_length': {'type': 'number'}, 'doc_preview': {}, 'avg_doc_length': {'type': 'number'}, 'documents_count': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['query', 'chunks'], 'properties': {'query': {'type': 'string', 'description': 'The user question to answer'}, 'chunks': {'type': 'array', 'items': {'type': 'object', 'properties': {'text': {'type': 'string'}, 'score': {'type': 'number'}, 'source': {'type': 'string'}}}, 'description': 'Retrieved context chunks with .text (required), .source (optional), .score (optional)'}, 'language': {'type': 'string', 'description': 'Response language instruction (e.g. "French", "Spanish")'}, 'cite_sources': {'type': 'boolean', 'description': 'Add [1], [2] citation numbers (default: true)'}, 'max_context_tokens': {'type': 'number', 'description': 'Max tokens for context section (default: 2000)'}, 'system_instruction': {'type': 'string', 'description': 'Custom system instruction (default: standard RAG grounding instruction)'}}}

{'type': 'object', 'properties': {'prompt': {}, 'system_prompt': {}, 'chunks_included': {'type': 'number'}, 'included_chunks': {}, 'chunks_truncated': {'type': 'number'}, 'total_tokens_estimate': {'type': 'number'}, 'context_tokens_estimate': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'Text to analyze for readability'}}}

{'type': 'object', 'properties': {'level': {}, 'stats': {'type': 'object'}, 'coleman_liau_index': {'type': 'number'}, 'flesch_reading_ease': {}, 'flesch_kincaid_grade': {'type': 'number'}, 'automated_readability_index': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input', 'to'], 'properties': {'to': {'type': 'string', 'description': 'Target case: "camel", "pascal", "snake", "kebab", "upper_snake", "dot", "title"'}, 'input': {'type': 'string', 'description': 'String to convert (e.g., "myVariableName", "my-css-class")'}}}

{'type': 'object', 'properties': {'result': {}, 'from_words': {}, 'target_case': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['foreground', 'background'], 'properties': {'background': {'type': 'string', 'description': 'Background color in hex (e.g., "#ffffff")'}, 'foreground': {'type': 'string', 'description': 'Foreground color in hex (e.g., "#333333")'}}}

{'type': 'object', 'properties': {'ratio': {}, 'AA_large': {'type': 'boolean'}, 'AAA_large': {'type': 'boolean'}, 'AA_normal': {'type': 'boolean'}, 'AAA_normal': {'type': 'boolean'}, 'background': {'type': 'object'}, 'foreground': {'type': 'object'}, 'ratio_text': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'Color value to convert, e.g. "#ff6b6b", "rgb(255,107,107)", "hsl(0,100%,71%)"'}}}

{'type': 'object', 'properties': {'b': {}, 'g': {}, 'r': {}, 'hex': {}, 'hsl': {'type': 'string'}, 'rgb': {'type': 'string'}, 'input': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['models'], 'properties': {'models': {'type': 'array', 'items': {'type': 'string'}, 'description': 'Array of 2-5 model names (e.g. ["gpt-4o","claude-3.5-sonnet","gemini-2.0-flash"])'}, 'use_case': {'enum': ['cost', 'context', 'reasoning', 'multimodal', 'speed'], 'type': 'string', 'description': 'Optimize recommendation for this criterion'}}}

{'type': 'object', 'properties': {'rows': {}, 'model': {}, 'use_case': {}, 'recommendation': {}, 'models_compared': {'type': 'number'}, 'cost_per_1k_total': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['response_a', 'response_b'], 'properties': {'task': {'type': 'string', 'description': 'The task/prompt both outputs were answering — used by the LLM judge for context'}, 'model': {'type': 'string', 'description': 'Optional judge model id (BYOK). When set with api_key, an LLM judge picks a qualitative winner.'}, 'api_key': {'type': 'string', 'description': 'Optional API key for the judge model (BYOK). Used only for the judge call; never stored.'}, 'label_a': {'type': 'string', 'description': 'Label for output A (e.g. "GPT-4o", "v1.0")'}, 'label_b': {'type': 'string', 'description': 'Label for output B (e.g. "GPT-5-nano", "v1.1")'}, 'reference': {'type': 'string', 'description': 'Optional ground-truth / expected answer. If set, each output is scored against it and the closer one wins (deterministic).'}, 'check_json': {'type': 'boolean', 'description': 'Try to parse as JSON and compare structurally (keys, types, values)'}, 'response_a': {'type': 'string', 'description': "First output (e.g. model A's answer)"}, 'response_b': {'type': 'string', 'description': "Second output (e.g. model B's answer)"}}}

{'type': 'object', 'properties': {'judge': {}, 'labelA': {}, 'labelB': {}, 'metrics': {}, 'summary': {'type': 'string'}, 'verdict': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['responses'], 'properties': {'responses': {'type': 'array', 'items': {'type': 'string'}, 'description': 'Array of 2+ LLM responses to compare (same prompt, different runs)'}, 'check_facts': {'type': 'boolean', 'description': 'Check for contradictory numbers/facts across responses (default: true)'}}}

{'type': 'object', 'properties': {'verdict': {}, 'fact_drift': {}, 'avg_similarity': {}, 'response_count': {'type': 'number'}, 'pairwise_scores': {}, 'fact_contradiction': {}, 'length_variance_percent': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['messages', 'model'], 'properties': {'model': {'type': 'string', 'description': 'Target model name (e.g. gpt-4o, claude-3.5-sonnet)'}, 'messages': {'type': 'array', 'items': {'type': 'object', 'properties': {'role': {'type': 'string'}, 'content': {'type': 'string'}}}, 'description': 'Array of messages (system/user/assistant)'}, 'max_output_tokens': {'type': 'number', 'description': 'Reserved tokens for output (default: 4096)'}}}

{'type': 'object', 'properties': {'fits': {}, 'role': {}, 'chars': {'type': 'number'}, 'index': {}, 'model': {}, 'tokens': {}, 'warnings': {}, 'breakdown': {'type': 'object'}, 'per_message': {}, 'total_tokens': {}, 'message_count': {'type': 'number'}, 'context_window': {}, 'total_input_tokens': {}, 'utilization_percent': {'type': 'string'}, 'reserved_output_tokens': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['messages'], 'properties': {'messages': {'type': 'array', 'items': {'type': 'object', 'properties': {'role': {'enum': ['system', 'user', 'assistant'], 'type': 'string'}, 'content': {'type': 'string'}}}, 'description': 'Conversation messages in order'}}}

{'type': 'object', 'properties': {'turn_count': {'type': 'number'}, 'repetitions': {}, 'topic_drift': {}, 'user_messages': {'type': 'number'}, 'context_retention': {}, 'has_system_prompt': {'type': 'boolean'}, 'assistant_messages': {'type': 'number'}, 'avg_response_length': {'type': 'number'}, 'repetition_detected': {'type': 'boolean'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['url'], 'properties': {'url': {'type': 'string', 'description': 'Full URL to audit (e.g. https://example.com/login)'}}}

{'type': 'object', 'properties': {'url': {}, 'name': {}, 'path': {}, 'score': {'type': 'number'}, 'domain': {}, 'issues': {}, 'secure': {}, 'cookies': {'type': 'array'}, 'max_age': {}, 'message': {'type': 'string'}, 'httpOnly': {}, 'sameSite': {}, 'host_prefix': {}, 'cookies_found': {'type': 'number'}, 'secure_prefix': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['url'], 'properties': {'url': {'type': 'string', 'description': 'Full URL to test, e.g. https://api.example.com/resource'}, 'method': {'type': 'string', 'description': 'HTTP method to simulate (default: GET)'}, 'origin': {'type': 'string', 'description': 'Origin header to simulate (default: https://yourdomain.com)'}}}

{'type': 'object', 'properties': {'url': {}, 'method': {}, 'status': {}, 'preflight': {}, 'allHeaders': {}, 'corsHeaders': {}, 'testedOrigin': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['url'], 'properties': {'url': {'type': 'string', 'description': 'Full URL to test (e.g. https://api.example.com/endpoint)'}, 'origin': {'type': 'string', 'description': 'Custom Origin header to test (default: tests multiple origins automatically)'}}}

{'type': 'object', 'properties': {'url': {}, 'error': {'type': 'string'}, 'tests': {}, 'warning': {'type': 'string'}, 'risk_level': {'enum': ['safe', 'low', 'medium', 'high', 'critical', 'unknown']}, 'origins_tested': {'type': 'number'}, 'total_findings': {'type': 'number'}, 'origins_reachable': {'type': 'number'}, 'origins_conclusive': {'type': 'number'}, 'origins_inconclusive': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['reasoning'], 'properties': {'reasoning': {'type': 'string', 'description': 'The CoT / reasoning trace text (e.g. from <think> tags or step-by-step output)'}, 'expected_conclusion': {'type': 'string', 'description': 'Expected final answer to check against (optional)'}}}

{'type': 'object', 'properties': {'markers': {}, 'step_count': {'type': 'number'}, 'total_chars': {'type': 'number'}, 'total_lines': {'type': 'number'}, 'has_conclusion': {'type': 'boolean'}, 'reasoning_depth': {}, 'backtracking_signals': {}, 'reasoning_depth_label': {}, 'conclusion_matches_expected': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'Source code to analyze'}, 'language': {'type': 'string', 'description': 'Language hint: "js", "ts", "py", "java", "c", "rb", "go", "sh", "html", "css" (auto-detect if omitted)'}}}

{'type': 'object', 'properties': {'language': {}, 'code_lines': {}, 'blank_lines': {}, 'total_lines': {}, 'comment_lines': {}, 'comment_density': {}, 'code_to_comment_ratio': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'Text to count tokens for'}}}

{'type': 'object', 'properties': {'chars': {}, 'words': {}, 'tokens_estimate': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['confluence_base_url', 'confluence_email', 'confluence_token', 'space_key', 'test_suite'], 'properties': {'title': {'type': 'string', 'description': 'Page title. Defaults to "Test Plan: {issue_key}"'}, 'issue_key': {'type': 'string', 'description': 'Source Jira issue key (for the page title and source link)'}, 'issue_url': {'type': 'string', 'description': 'Source Jira issue URL (added as a link in the page)'}, 'space_key': {'type': 'string', 'description': 'Confluence space key where the page will be created, e.g. "QA", "ENG"'}, 'test_suite': {'type': 'object', 'description': 'The test_suite object from jira_to_test_suite result', 'additionalProperties': True}, 'parent_page_id': {'type': 'string', 'description': 'Optional parent page ID — page will be created as a child of this page'}, 'confluence_email': {'type': 'string', 'description': 'Atlassian account email'}, 'confluence_token': {'type': 'string', 'description': 'Atlassian API token'}, 'confluence_base_url': {'type': 'string', 'description': 'Atlassian base URL'}}}

{'type': 'object', 'properties': {'title': {'type': 'string'}, 'page_id': {'type': 'string'}, 'success': {'type': 'boolean'}, 'page_url': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['expression'], 'properties': {'expression': {'type': 'string', 'description': 'Cron expression (e.g., "0 9 * * 1-5", "*/15 * * * *")'}}}

{'type': 'object', 'properties': {'fields': {'type': 'object'}, 'expression': {}, 'human_readable': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['expression'], 'properties': {'expression': {'type': 'string', 'description': 'Cron expression with 5 fields, e.g. "*/15 9-18 * * 1-5"'}, 'next_runs_count': {'type': 'number', 'description': 'How many upcoming runs to return (1-50, default: 10)'}}}

{'type': 'object', 'properties': {'valid': {'type': 'boolean'}, 'fields': {'type': 'object'}, 'next_runs': {}, 'expression': {}, 'human_readable': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['token'], 'properties': {'token': {'type': 'string', 'description': 'The JWT string to decode (header.payload.signature)'}}}

{'type': 'object', 'properties': {'note': {'type': 'string'}, 'header': {}, 'expired': {}, 'payload': {}, 'expiresAt': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'Text to detect language from (min 20 chars for accuracy)'}}}

{'type': 'object', 'properties': {'lang': {}, 'name': {'type': 'string'}, 'score': {}, 'method': {'type': 'string'}, 'matched': {}, 'language': {'type': 'string'}, 'confidence': {'type': 'number'}, 'top_candidates': {'type': 'array'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'Code or config content to scan (max 500KB)'}, 'filename': {'type': 'string', 'description': 'Optional filename for context (e.g. ".env", "config.js")'}}}

{'type': 'object', 'properties': {'filename': {}, 'findings': {}, 'risk_level': {}, 'recommendation': {}, 'total_findings': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['before', 'after'], 'properties': {'after': {'type': 'object', 'description': 'Current page mapping: same shape as before, captured after the UI change.'}, 'before': {'type': 'object', 'description': 'Baseline page mapping: { page, url, capturedAt, elements: [{role, name, selector, context?}] }. Captured before a UI change.'}}}

{'type': 'object', 'properties': {'rows': {'type': 'array'}, 'added': {'type': 'array'}, 'counts': {'type': 'object'}, 'verdict': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['a', 'b'], 'properties': {'a': {'type': 'string', 'description': 'Original (before) text'}, 'b': {'type': 'string', 'description': 'Modified (after) text'}, 'context': {'type': 'number', 'description': 'Context lines around each change (0–20, default: 3)'}}}

{'type': 'object', 'properties': {'diff': {'type': 'string'}, 'added': {'type': 'number'}, 'removed': {'type': 'number'}, 'unchanged': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'properties': {'batch': {'type': 'array', 'items': {'type': 'object', 'required': ['text_a', 'text_b'], 'properties': {'text_a': {'type': 'string'}, 'text_b': {'type': 'string'}}}, 'description': 'Batch mode: array of { text_a, text_b } pairs. Overrides text_a/text_b if provided.'}, 'text_a': {'type': 'string', 'description': 'First text to compare (single-pair mode)'}, 'text_b': {'type': 'string', 'description': 'Second text to compare (single-pair mode)'}, 'methods': {'type': 'array', 'items': {'enum': ['bow', 'tfidf', 'ngram'], 'type': 'string'}, 'description': 'Algorithms to use (default: all three). Options: "bow", "tfidf", "ngram"'}}}

{'type': 'object', 'properties': {'mode': {'type': 'string'}, 'count': {'type': 'number'}, 'scores': {}, 'text_a': {}, 'text_b': {}, 'results': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': '.env file content to parse (e.g. the output of `cat .env`)'}}}

{'type': 'object', 'properties': {'vars': {}, 'count': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'String to HTML-escape'}}}

{'type': 'object', 'properties': {'escaped': {}, 'original_length': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['model', 'input_tokens'], 'properties': {'model': {'type': 'string', 'description': 'Model name, e.g. "gpt-4o", "claude-3.5-sonnet", "deepseek-v3"'}, 'input_tokens': {'type': 'number', 'description': 'Number of input/prompt tokens'}, 'output_tokens': {'type': 'number', 'description': 'Number of output/completion tokens (default: 0)'}}}

{'type': 'object', 'properties': {'model': {}, 'rates': {'type': 'object'}, 'input_tokens': {}, 'output_tokens': {}, 'input_cost_usd': {'type': 'string'}, 'total_cost_usd': {'type': 'string'}, 'output_cost_usd': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'Raw text (e.g., LLM output) that may contain a JSON object or array'}}}

{'type': 'object', 'properties': {'json': {}, 'source': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input', 'path'], 'properties': {'path': {'type': 'string', 'description': 'Dot-notation path, e.g. "user.address.city" or "items.0.name"'}, 'input': {'type': ['string', 'object', 'array'], 'description': 'The JSON to traverse — a JSON string, or the object/array itself.'}}}

{'type': 'object', 'properties': {'path': {}, 'type': {}, 'value': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'Text to extract links from'}, 'types': {'type': 'array', 'items': {'enum': ['url', 'email', 'domain'], 'type': 'string'}, 'description': 'Types to extract (default: all three)'}}}

{'type': 'object', 'properties': {'total': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'tags': {'type': 'array', 'items': {'type': 'string'}, 'description': 'Custom tags to add (default set: TODO, FIXME, HACK, NOTE, BUG, OPTIMIZE, XXX)'}, 'input': {'type': 'string', 'description': 'Code or text to scan'}, 'include_context': {'type': 'boolean', 'description': 'Include full line text (default: true)'}}}

{'type': 'object', 'properties': {'items': {}, 'total': {'type': 'number'}, 'counts': {}, 'has_critical': {'type': 'boolean'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['confluence_base_url', 'confluence_email', 'confluence_token'], 'properties': {'page_id': {'type': 'string', 'description': 'Confluence page ID (numeric string), e.g. "123456789"'}, 'page_url': {'type': 'string', 'description': 'Full Confluence page URL (alternative to page_id), e.g. "https://mycompany.atlassian.net/wiki/spaces/ENG/pages/123456789"'}, 'confluence_email': {'type': 'string', 'description': 'Atlassian account email (same credentials as Jira)'}, 'confluence_token': {'type': 'string', 'description': 'Atlassian API token'}, 'include_children': {'type': 'boolean', 'description': 'List direct child pages (id + title) (default: false)'}, 'confluence_base_url': {'type': 'string', 'description': 'Atlassian base URL, e.g. "https://mycompany.atlassian.net"'}}}

{'type': 'object', 'properties': {'url': {'type': 'string'}, 'title': {'type': 'string'}, 'page_id': {'type': 'string'}, 'children': {'type': 'array', 'items': {'type': 'object'}}, 'markdown': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['issue_key', 'jira_base_url', 'jira_email', 'jira_token'], 'properties': {'fields': {'type': 'array', 'items': {'type': 'string'}, 'description': 'Specific Jira field names to return. Omit for all standard fields.'}, 'issue_key': {'type': 'string', 'description': 'Jira issue key, e.g. "PROJ-123"'}, 'jira_email': {'type': 'string', 'description': 'Atlassian account email'}, 'jira_token': {'type': 'string', 'description': 'Atlassian API token (from id.atlassian.com > Security > API tokens)'}, 'jira_base_url': {'type': 'string', 'description': 'Atlassian base URL, e.g. "https://mycompany.atlassian.net"'}, 'include_comments': {'type': 'boolean', 'description': 'Include issue comments, up to 20 (default: true)'}, 'include_attachments': {'type': 'boolean', 'description': 'Include attachment metadata list (default: false)'}}}

{'type': 'object', 'properties': {'key': {'type': 'string'}, 'url': {'type': 'string'}, 'type': {'type': 'string'}, 'labels': {'type': 'array', 'items': {'type': 'string'}}, 'status': {'type': 'string'}, 'summary': {'type': 'string'}, 'assignee': {'type': 'string'}, 'priority': {'type': 'string'}, 'reporter': {'type': 'string'}, 'description': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'properties': {'limit': {'type': 'number', 'description': 'Max articles to return (default: 20, max: 50)'}, 'category': {'type': 'string', 'description': 'Filter: "qa" (testing/quality), "ai" (AI/LLM/agents), "all" (default — both)'}}}

{'type': 'object', 'properties': {'articles': {'type': 'array'}, 'category': {}, 'total_found': {'type': 'number'}, 'sources_queried': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['examples'], 'properties': {'format': {'enum': ['chat', 'xml', 'markdown', 'plain'], 'type': 'string', 'description': 'Output format (default: chat)'}, 'examples': {'type': 'array', 'items': {'type': 'object', 'properties': {'input': {'type': 'string'}, 'label': {'type': 'string'}, 'output': {'type': 'string'}}}, 'description': 'Array of {input, output} pairs'}, 'input_label': {'type': 'string', 'description': 'Label for input (default: User / <input>)'}, 'output_label': {'type': 'string', 'description': 'Label for output (default: Assistant / <output>)'}}}

{'type': 'object', 'properties': {'format': {}, 'formatted': {}, 'example_count': {'type': 'number'}, 'token_estimate': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['query'], 'properties': {'query': {'type': 'string', 'description': 'Keyword(s) to search in tool name and description (e.g. "cors", "token", "vector", "json")'}, 'category': {'type': 'string', 'description': 'Optional: filter by category — data | encoding | text | llm | qa | rag | dev | security | web'}, 'max_results': {'type': 'number', 'description': 'Maximum tools to return (default 10, max 50). Results are ranked by IDF-weighted relevance, so common words like "test" do not inflate the list.'}, 'with_schema': {'type': 'boolean', 'description': 'Set true to include inputSchema in results (default: false)'}}}

{'type': 'object', 'properties': {'hint': {}, 'tool': {}, 'count': {'type': 'number'}, 'query': {}, 'score': {}, 'tools': {'type': 'array'}, 'category': {}, 'truncated': {'type': 'boolean'}, 'total_matches': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['gherkin', 'warnings', 'api_key', 'model'], 'properties': {'model': {'type': 'string', 'description': 'LLM model to use for the fix, e.g. "gpt-4o-mini". Must belong to the provider whose key you passed in api_key.'}, 'api_key': {'type': 'string', 'description': 'Your own LLM provider API key (BYOK) — OpenAI "sk-…", Anthropic "sk-ant-…", Google "AIzaSy…", or Groq "gsk_…". There is no server-side key for this tool: if you do not have one, do not call it and do not invent a value — placeholders like "configured", "your_api_key" or a masked "sk-…***…" are rejected. Used for this call only, never stored.'}, 'gherkin': {'type': 'string', 'description': 'The current Gherkin text from the jira_to_test_suite result (test_suite.gherkin).'}, 'warnings': {'type': 'array', 'items': {'type': 'string'}, 'description': 'The _gherkin_warnings array from the jira_to_test_suite result.'}}}

{'type': 'object', 'properties': {'latency_ms': {'type': 'number'}, 'model_used': {'type': 'string'}, 'fixed_gherkin': {'type': 'string'}, 'warnings_after': {'type': 'number'}, 'warnings_before': {'type': 'number'}, 'remaining_warnings': {'type': 'array', 'items': {'type': 'string'}}}}

{'type': 'object', 'required': ['input'], 'properties': {'mode': {'type': 'string', 'description': '"flatten" (default) or "unflatten"'}, 'input': {'type': ['string', 'object', 'array'], 'description': 'The JSON to flatten or unflatten — a JSON string, or the object itself.'}, 'separator': {'type': 'string', 'description': 'Key separator (default: ".")'}}}

{'type': 'object', 'properties': {'result': {}, 'key_count': {'type': 'number'}, 'max_depth': {'type': 'array'}}, 'additionalProperties': True}

{'type': 'object', 'properties': {'bytes': {'type': 'number', 'description': 'Number of bytes to format'}, 'standard': {'enum': ['both', 'si', 'iec'], 'type': 'string', 'description': 'Output standard (default: both)'}, 'size_string': {'type': 'string', 'description': 'Size string to parse to bytes (e.g. "1.5 GB", "512 MiB")'}}}

{'type': 'object', 'properties': {'bytes': {'type': 'number'}, 'original': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'A raw JSON string, e.g. \'{"key":"value"}\'. Must already parse as JSON — plain text or truncated JSON is rejected, not repaired.'}, 'indent': {'type': 'number', 'description': 'Indent size (default: 2)'}}}

{'type': 'object', 'properties': {'valid': {'type': 'boolean'}, 'formatted': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': ['string', 'object', 'array'], 'description': 'The array of objects to render — a JSON string, or the array itself.'}, 'columns': {'type': 'array', 'items': {'type': 'string'}, 'description': 'Column names and order (default: all keys from first row)'}}}

{'type': 'object', 'properties': {'rows': {'type': 'number'}, 'table': {'type': 'string'}, 'columns': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['function_call', 'allowed_functions'], 'properties': {'function_call': {'type': 'object', 'description': 'The function call object from LLM (e.g. { "name": "get_weather", "arguments": {"city":"Paris"} })', 'additionalProperties': True}, 'allowed_functions': {'type': 'array', 'items': {'type': 'object', 'properties': {'name': {'type': 'string'}, 'optional_args': {'type': 'array', 'items': {'type': 'string'}}, 'required_args': {'type': 'array', 'items': {'type': 'string'}}}}, 'description': 'List of allowed function definitions'}}}

{'type': 'object', 'properties': {'valid': {'type': 'boolean'}, 'errors': {'type': 'array'}, 'error_count': {'type': 'number'}, 'function_name': {}, 'provided_args': {}, 'required_args': {}}, 'additionalProperties': True}

{'type': 'object', 'properties': {'cron': {'type': 'string', 'description': "Cron expression when triggers include 'schedule' (default: '0 6 * * 1' — Mondays 06:00 UTC)."}, 'gate': {'enum': ['eval_contract', 'cli_checks', 'both', 'selector_drift', 'all'], 'type': 'string', 'description': 'Which gate to emit. eval_contract = LLM eval via the action (default). cli_checks = deterministic CLI assertions. selector_drift = an E2E selector-drift gate via @ia-qa/self-healing (boots the app, captures, diffs against the committed baseline, branches on exit code 0/1/2). both = CLI checks + eval. all = CLI checks, then drift, then eval.'}, 'provider': {'enum': ['groq', 'openai', 'anthropic', 'google'], 'type': 'string', 'description': 'LLM provider the contract runs against — decides which repository secret the workflow wires (default: groq).'}, 'triggers': {'type': 'array', 'items': {'enum': ['push', 'pull_request', 'workflow_dispatch', 'schedule'], 'type': 'string'}, 'description': 'Workflow triggers (default: push + pull_request).'}, 'cli_tools': {'type': 'array', 'items': {'type': 'string'}, 'description': 'IA-QA tool names to run as deterministic gates, e.g. ["secret_scan","prompt_injection_scan"]. Tools with no known CI recipe get a --stdin step flagged in notes.'}, 'min_score': {'type': 'number', 'description': 'Override the contract min_score (0-100). Omit to use the value in the contract.'}, 'app_base_url': {'type': 'string', 'description': 'URL the drift gate waits for before capturing (default: http://127.0.0.1:3000). Must match config.baseUrl in .ia-qa/config.json.'}, 'fail_on_fail': {'type': 'boolean', 'description': 'Fail the build on a FAIL/PARTIAL verdict (default: true). Set false to report without gating.'}, 'node_version': {'type': 'string', 'description': 'Node version for the CLI steps (default: "20").'}, 'contract_path': {'type': 'string', 'description': 'Path to the .ia-eval.yaml contract, relative to the repo root (default: evals/smoke.ia-eval.yaml). Only used when the gate includes eval_contract.'}, 'workflow_name': {'type': 'string', 'description': 'Workflow display name (default: "IA-QA Quality Gate").'}, 'app_start_command': {'type': 'string', 'description': 'Command that boots the app for the selector_drift gate, e.g. "npm run start:ci". Cannot be guessed — omitted, the step carries an explicit TODO and the note says so, because a plausible default would silently map nothing.'}}}

{'type': 'object', 'properties': {'gate': {'type': 'string'}, 'path': {'type': 'string'}, 'yaml': {'type': 'string'}, 'notes': {'type': 'array', 'items': {'type': 'string'}}, 'next_steps': {'type': 'array', 'items': {'type': 'string'}}, 'secrets_required': {'type': 'array', 'items': {'type': 'string'}}}, 'additionalProperties': True}

{'type': 'object', 'required': ['url'], 'properties': {'url': {'type': 'string', 'description': 'Request URL (must be http/https)'}, 'body': {'type': 'string', 'description': 'Raw request body string'}, 'method': {'type': 'string', 'description': 'HTTP method (default: GET)'}, 'headers': {'type': 'object', 'description': 'Request headers as key-value object', 'additionalProperties': True}, 'verbose': {'type': 'boolean', 'description': 'Add -v for verbose output (default: false)'}, 'body_json': {'type': 'object', 'description': 'JSON body (auto-adds Content-Type: application/json)', 'additionalProperties': True}, 'follow_redirects': {'type': 'boolean', 'description': 'Follow redirects with -L flag (default: true)'}}}

{'type': 'object', 'properties': {'url': {}, 'curl': {'type': 'string'}, 'method': {}, 'header_count': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['description'], 'properties': {'task_type': {'enum': ['rag', 'summarization', 'classification', 'safety', 'customer_support', 'code_gen'], 'type': 'string', 'description': 'Optional task type hint to guide evaluator selection.'}, 'description': {'type': 'string', 'description': 'Plain-language description of what the LLM under test should do. Be specific: describe inputs, expected behaviour, and constraints.'}, 'system_prompt': {'type': 'string', 'description': 'Optional system prompt of the LLM under test. Helps generate more accurate test cases.'}, 'scenario_count': {'enum': [3, 5, 8], 'type': 'number', 'description': 'Number of scenarios to generate (default: 5). Covers happy path + edge cases + adversarial.'}}}

{'type': 'object', 'properties': {'yaml': {'type': 'string'}, 'task_type': {'type': 'string'}, 'model_used': {'type': 'string'}, 'scenario_count': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['message', 'secret'], 'properties': {'secret': {'type': 'string', 'description': 'Secret key'}, 'message': {'type': 'string', 'description': 'Message to sign'}, 'encoding': {'enum': ['hex', 'base64', 'base64url'], 'type': 'string', 'description': 'Output encoding (default: hex)'}, 'algorithm': {'type': 'string', 'description': 'Hash algorithm: sha256 (default), sha512, sha1, md5'}}}

{'type': 'object', 'properties': {'hmac': {}, 'encoding': {}, 'algorithm': {}, 'message_length': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['results'], 'properties': {'results': {'type': 'object', 'description': 'The JSON object returned by run_eval_contract()', 'additionalProperties': True}}}

{'type': 'object', 'properties': {'html': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['type'], 'properties': {'type': {'type': 'string', 'description': 'Schema @type: "WebSite", "FAQPage", "Article", "Person", "Organization", "SoftwareApplication", "HowTo"'}, 'fields': {'type': 'object', 'description': 'Schema fields as key-value pairs (name, url, description, author, datePublished, etc.)', 'additionalProperties': True}, 'faq_items': {'type': 'array', 'items': {'type': 'object', 'properties': {'answer': {'type': 'string'}, 'question': {'type': 'string'}}}, 'description': 'For FAQPage/HowTo: array of { question, answer } objects'}}}

{'type': 'object', 'properties': {'name': {'type': 'string'}, 'schema': {}, 'snippet': {'type': 'string'}, 'acceptedAnswer': {'type': 'object'}}, 'additionalProperties': True}

{'type': 'object', 'properties': {'length': {'type': 'number', 'description': 'Password length (4–128, default: 16)'}, 'numbers': {'type': 'boolean', 'description': 'Include digits (default: true)'}, 'symbols': {'type': 'boolean', 'description': 'Include symbols like !@#$ (default: false)'}, 'uppercase': {'type': 'boolean', 'description': 'Include uppercase letters (default: true)'}}}

{'type': 'object', 'properties': {'length': {'type': 'number'}, 'password': {}, 'charset_size': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'String to slugify'}, 'separator': {'type': 'string', 'description': 'Separator character (default: "-")'}}}

{'type': 'object', 'properties': {'slug': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['feature'], 'properties': {'inputs': {'type': 'string', 'description': 'Optional: list of input parameters (one per line, e.g. "email: string [required]", "password: string [required, min 8 chars]", "age: number [18-99]")'}, 'feature': {'type': 'string', 'description': 'Feature or function to test. Be specific: describe inputs, expected behaviour, context. Constraints stated here ("password must be at least 8 characters") are used when the sentence names exactly one field.'}}}

{'type': 'object', 'properties': {'feature': {'type': 'string'}, 'test_cases': {'type': 'array', 'items': {'type': 'object'}}, 'parsedInputs': {'type': 'array', 'items': {'type': 'object'}}, 'gherkinFormat': {'type': 'string'}, 'gherkinScenarioCount': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'properties': {'count': {'type': 'number', 'description': 'Number of UUIDs to generate (1–100, default: 1)'}}}

{'type': 'object', 'properties': {'count': {'type': 'number'}, 'uuids': {}}, 'additionalProperties': True}

{'type': 'object', 'properties': {'topic': {'enum': ['start-here', 'llm-unit-testing', 'rag-pipeline', 'prompt-stability', 'prompt-ab-testing', 'embedding-quality', 'eval-framework', 'semantic-testing', 'auto-testing', 'security', 'api-testing', 'ci-cd', 'multimodal', 'llm-data-security', 'agent-observability', 'pro-tips', 'learning-paths', 'golden-dataset', 'selector-drift', 'qa-recipes', 'playbooks'], 'type': 'string', 'description': 'The testing topic to retrieve guidelines for. Omit to get the start-here map and the full list of available topics.'}}}

{'type': 'object', 'properties': {'tip': {'type': 'string'}, 'topic': {}, 'usage': {'type': 'string'}, 'keywords': {'type': 'array'}, 'start_here': {'type': 'object'}, 'available_topics': {'type': 'array'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['response', 'rules'], 'properties': {'rules': {'type': 'array', 'items': {'type': 'object', 'properties': {'type': {'enum': ['must_include', 'must_not_include', 'max_length', 'min_length', 'format', 'regex_match', 'regex_not_match', 'starts_with', 'ends_with', 'word_count_max', 'word_count_min'], 'type': 'string'}, 'label': {'type': 'string', 'description': 'Optional human-readable label'}, 'value': {'type': 'string', 'description': 'Value for the rule (text, number as string, regex, or format name)'}}}, 'description': 'Array of guardrail rules to check'}, 'response': {'type': 'string', 'description': 'The LLM response to test'}}}

{'type': 'object', 'properties': {'pass': {'type': 'boolean'}, 'rule': {}, 'label': {}, 'value': {}, 'detail': {'type': 'string'}, 'failed': {}, 'passed': {}, 'results': {}, 'all_passed': {'type': 'boolean'}, 'total_rules': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['answer', 'context'], 'properties': {'answer': {'type': 'string', 'description': 'The LLM-generated answer to verify'}, 'strict': {'type': 'boolean', 'description': 'If true, every sentence in the answer must be supported (default: false)'}, 'context': {'type': 'string', 'description': 'The source/reference text that should ground the answer'}}}

{'type': 'object', 'properties': {'detail': {'type': 'string'}, 'message': {'type': 'string'}, 'numbers': {}, 'overlap': {'type': 'number'}, 'verdict': {'type': 'string'}, 'analysis': {}, 'entities': {}, 'grounded': {'type': 'boolean'}, 'sentence': {}, 'total_words': {'type': 'number'}, 'matched_words': {'type': 'number'}, 'contradictions': {}, 'grounded_count': {'type': 'number'}, 'unbound_claims': {}, 'grounding_score': {}, 'total_sentences': {'type': 'number'}, 'ungrounded_count': {'type': 'number'}, 'unsupported_claims': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'Text to hash'}, 'algorithm': {'type': 'string', 'description': 'Hash algorithm: sha256 (default), sha512, sha1, md5'}}}

{'type': 'object', 'properties': {'hash': {}, 'algorithm': {}, 'input_length': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'HTML string to convert'}, 'strip_links': {'type': 'boolean', 'description': 'Strip link URLs, keep text only (default: false)'}}}

{'type': 'object', 'properties': {'markdown': {}, 'markdown_length': {'type': 'number'}, 'original_length': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['code'], 'properties': {'code': {'type': 'number', 'description': 'HTTP status code (e.g. 200, 404, 429, 503)'}}}

{'type': 'object', 'properties': {'code': {}, 'desc': {'type': 'string'}, 'name': {'type': 'string'}, 'class': {}, 'cacheable': {}, 'registered': {'type': 'boolean'}, 'description': {}}, 'additionalProperties': True}

{'type': 'object', 'properties': {'_meta': {'type': 'object', 'properties': {'agent': {'type': 'string'}, 'model': {'type': 'string'}, 'version': {'type': 'string'}}, 'description': 'Optional self-identification. Keys: agent (string), model (string), version (string).'}}}

{'type': 'object', 'properties': {'note': {'type': 'string'}, 'session': {'type': 'object'}, 'meta_override': {'type': 'object'}, 'effective_agent': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['api_key', 'model'], 'properties': {'issue': {'type': 'object', 'description': 'Pre-fetched issue object from fetch_jira_issue, OR a mock object with fields: key, summary, description (plain text or Markdown), status, issue_type, priority, labels, comments. Use this for offline/CI testing without Jira credentials.', 'additionalProperties': True}, 'model': {'type': 'string', 'description': 'LLM model to use, e.g. "gpt-4o-mini", "claude-3-5-haiku-20241022", "gemini-2.0-flash".'}, 'api_key': {'type': 'string', 'description': 'Your LLM provider API key (OpenAI sk-, Anthropic sk-ant-, Google AIzaSy-, etc.).'}, 'issue_key': {'type': 'string', 'description': 'Jira issue key to fetch automatically, e.g. "PROJ-123". Required if issue is not provided.'}, 'jira_email': {'type': 'string', 'description': 'Atlassian account email. Required for auto-fetch mode.'}, 'jira_token': {'type': 'string', 'description': 'Atlassian API token. Required for auto-fetch mode.'}, 'max_tokens': {'type': 'integer', 'default': 8192, 'description': 'Maximum tokens for the LLM response. Default: 8192. Increase for large tickets with many ACs; decrease to reduce cost on simple tickets.'}, 'jira_base_url': {'type': 'string', 'description': 'Atlassian base URL. Required for auto-fetch mode.'}, 'confluence_pages': {'type': 'array', 'items': {'type': 'object', 'additionalProperties': True}, 'description': 'Optional array of pre-fetched Confluence page objects from fetch_confluence_page, used as documentation context.'}}}

{'type': 'object', 'properties': {'summary': {'type': 'string'}, 'issue_key': {'type': 'string'}, 'issue_url': {'type': 'string'}, 'latency_ms': {'type': 'number'}, 'model_used': {'type': 'string'}, 'test_suite': {'type': 'object'}, 'tokens_used': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['before', 'after'], 'properties': {'after': {'type': ['string', 'object', 'array'], 'description': 'The modified JSON (after) — a JSON string, or the value itself.'}, 'before': {'type': ['string', 'object', 'array'], 'description': 'The original JSON (before) — a JSON string, or the value itself.'}, 'max_depth': {'type': 'number', 'description': 'Max nesting depth to recurse (default: 10)'}}}

{'type': 'object', 'properties': {'added': {'type': 'boolean'}, 'changes': {'type': 'array'}, 'removed': {'type': 'boolean'}, 'modified': {'type': 'boolean'}, 'identical': {'type': 'boolean'}, 'total_changes': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': ['string', 'object', 'array'], 'description': 'The sample JSON value to infer the schema from — a JSON string, or the value itself.'}, 'required_all': {'type': 'boolean', 'description': 'Mark all detected object properties as required (default: true)'}}}

{'type': 'object', 'properties': {'type': {'type': 'string'}, 'items': {'type': 'object'}, 'format': {}, 'schema': {'type': 'object'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['value', 'schema'], 'properties': {'value': {'type': ['string', 'object', 'array'], 'description': 'The JSON value to validate — a JSON string, or the value itself.'}, 'schema': {'type': ['string', 'object', 'array'], 'description': 'The JSON Schema — a JSON string, or the schema object itself.'}}}

{'type': 'object', 'properties': {'valid': {'type': 'boolean'}, 'errors': {'type': 'array'}, 'error_count': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': ['string', 'object', 'array'], 'description': 'The array of objects to convert — a JSON string, or the array itself.'}, 'headers': {'type': 'boolean', 'description': 'Include header row (default: true)'}, 'delimiter': {'type': 'string', 'description': 'Column delimiter (default: ",")'}}}

{'type': 'object', 'properties': {'csv': {'type': 'string'}, 'rows': {'type': 'number'}, 'columns': {'type': 'number'}, 'column_names': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': ['string', 'object', 'array'], 'description': 'The JSON to convert to YAML — a JSON string, or the value itself.'}, 'indent': {'type': 'number', 'description': 'Indentation size in spaces (default: 2)'}}}

{'type': 'object', 'properties': {'yaml': {}, 'lines': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['endpoints'], 'properties': {'endpoints': {'type': ['string', 'array'], 'items': {'type': 'object', 'properties': {'url': {'type': 'string', 'description': 'Full URL to test'}, 'body': {'type': 'object', 'description': 'Request body for POST', 'additionalProperties': True}, 'label': {'type': 'string', 'description': 'Optional label for this endpoint'}, 'method': {'enum': ['GET', 'POST'], 'type': 'string', 'description': 'HTTP method (default: GET)'}, 'headers': {'type': 'object', 'description': 'Custom headers', 'additionalProperties': True}}}, 'description': 'Endpoints to benchmark. Accepts a single URL string, an array of URL strings, or an array of {url, method?, body?, headers?, label?} objects.'}, 'iterations': {'type': 'number', 'description': 'Number of iterations per endpoint (default: 3, max: 10)'}}}

{'type': 'object', 'properties': {'results': {'type': 'array', 'items': {'type': 'object'}}, 'iterations': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'properties': {'a': {'type': 'string', 'description': 'First string (single-pair mode)'}, 'b': {'type': 'string', 'description': 'Second string (single-pair mode)'}, 'batch': {'type': 'array', 'items': {'type': 'object', 'properties': {'a': {'type': 'string'}, 'b': {'type': 'string'}}}, 'description': 'Batch of {a,b} pairs (max 50)'}, 'case_insensitive': {'type': 'boolean', 'description': 'Ignore case differences (default: false)'}}}

{'type': 'object', 'properties': {'a': {}, 'b': {}, 'mode': {'type': 'string'}, 'count': {'type': 'number'}, 'results': {}, 'distance': {}, 'similarity': {'type': 'string'}, 'operations_needed': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['message'], 'properties': {'strict': {'type': 'boolean', 'description': 'Enforce strict rules: max 72-char subject, imperative mood check (default: false)'}, 'message': {'type': 'string', 'description': 'Git commit message to validate'}}}

{'type': 'object', 'properties': {'type': {}, 'scope': {}, 'score': {'type': 'number'}, 'valid': {'type': 'boolean'}, 'checks': {}, 'subject': {}, 'has_body': {'type': 'boolean'}, 'is_breaking_change': {'type': 'boolean'}}, 'additionalProperties': True}

{'type': 'object', 'properties': {'provider': {'type': 'string', 'description': 'Filter by provider name (case-insensitive). E.g. "Groq", "HuggingFace", "OpenAI", "Anthropic", "Google", "DeepSeek", "xAI", "Ollama". Omit for full catalog.'}}}

{'type': 'object', 'properties': {'total': {'type': 'number'}, 'filter': {}, 'models': {}, 'providers': {}}, 'additionalProperties': True}

{'type': 'object', 'properties': {'dir': {'type': 'string', 'description': 'Directory to scan (defaults to server CWD)'}}}

{'type': 'object', 'properties': {'dir': {'type': 'string'}, 'count': {'type': 'number'}, 'files': {'type': 'array', 'items': {'type': 'string'}}}, 'additionalProperties': True}

{'type': 'object', 'properties': {'mode': {'type': 'string', 'description': 'cloud (API models) or local (Ollama/self-hosted). Default: cloud'}, 'top_n': {'type': 'number', 'description': 'Number of recommendations to return (default: 5)'}, 'vram_gb': {'type': 'number', 'description': 'GPU VRAM in GB (only for mode=local). Default: 16'}, 'features': {'type': 'array', 'items': {'type': 'string'}, 'description': 'Required features: vision, function_calling, json_mode, streaming, reasoning'}, 'use_case': {'type': 'string', 'description': 'Primary use case: chatbot | code | rag | summarization | classification | reasoning | agents | multilingual'}, 'max_budget': {'type': 'number', 'description': 'Maximum monthly budget in USD (based on tokens_per_day)'}, 'quantization': {'type': 'string', 'description': 'Quantization (only for mode=local): Q4_K_M | Q8_0 | FP16. Default: Q4_K_M'}, 'tokens_per_day': {'type': 'number', 'description': 'Estimated daily token volume (default: 100000)'}}}

{'type': 'object', 'properties': {'mode': {'type': 'string'}, 'score': {'type': 'number'}, 'results': {'type': 'array'}, 'vram_gb': {}, 'use_case': {}, 'quantization': {}, 'tokens_per_day': {}, 'total_matching': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['output', 'expected_format'], 'properties': {'output': {'type': 'string', 'description': 'The LLM output to validate'}, 'regex_pattern': {'type': 'string', 'description': 'Custom regex pattern (only when expected_format is "regex")'}, 'expected_format': {'enum': ['json', 'markdown_heading', 'code_block', 'bullet_list', 'numbered_list', 'table', 'yaml', 'xml', 'regex'], 'type': 'string', 'description': 'Expected format'}}}

{'type': 'object', 'properties': {'valid': {'type': 'boolean'}, 'checks': {}, 'failed': {}, 'passed': {}, 'total_checks': {'type': 'number'}, 'expected_format': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['prompt'], 'properties': {'model': {'type': 'string', 'description': 'Model ID (default: "openai/gpt-oss-20b"). Server-keyed whitelist only — Groq: openai/gpt-oss-20b, openai/gpt-oss-120b, qwen/qwen3.6-27b; HuggingFace: Qwen/Qwen3-32B, meta-llama/Llama-3.3-70B-Instruct, deepseek-ai/DeepSeek-R1, google/gemma-3-27b-it, and more. Other ids from list_llm_models are BYOK-only and will be rejected.'}, 'prompt': {'type': 'string', 'description': 'The user prompt / instruction to send to the model'}, 'system': {'type': 'string', 'description': 'Optional system prompt to set context or persona'}, 'max_tokens': {'type': 'number', 'description': 'Maximum tokens to generate (default: 2048, max: 4096)'}, 'temperature': {'type': 'number', 'description': 'Sampling temperature 0.0–1.5 (default: 0.7)'}}}

{'type': 'object', 'properties': {'model': {}, 'usage': {}, 'content': {}, 'provider': {}, 'latency_ms': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['output', 'schema'], 'properties': {'output': {'type': 'string', 'description': 'The LLM JSON output (raw string, will be parsed)'}, 'schema': {'type': 'object', 'description': 'JSON Schema (draft-07 subset) to validate against', 'additionalProperties': True}}}

{'type': 'object', 'properties': {'valid': {'type': 'boolean'}, 'errors': {'type': 'array'}, 'error_count': {'type': 'number'}, 'parse_error': {}, 'parsed_type': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['output'], 'properties': {'output': {'type': 'string', 'description': 'The LLM output text to validate'}, 'max_length': {'type': 'number', 'description': 'Maximum character length for the output'}, 'min_length': {'type': 'number', 'description': 'Minimum character length for the output'}, 'check_safety': {'type': 'boolean', 'description': 'Check for PII patterns (emails, phones, SSN), profanity signals, and prompt leakage'}, 'must_include': {'type': 'string', 'description': 'Comma-separated strings that MUST appear in the output'}, 'expected_format': {'enum': ['json', 'markdown', 'code', 'plain', 'any'], 'type': 'string', 'description': 'Expected output format'}, 'must_not_include': {'type': 'string', 'description': 'Comma-separated strings that must NOT appear (e.g. "TODO, FIXME, undefined, NaN")'}, 'check_json_schema': {'type': 'string', 'description': 'If expected_format is JSON, provide required keys as comma-separated list to validate the structure'}, 'expected_language': {'type': 'string', 'description': 'Expected language of the output (en, fr, es, de…). Checks for common words.'}}}

{'type': 'object', 'properties': {'total': {'type': 'number'}, 'checks': {}, 'failed': {}, 'passed': {}, 'verdict': {}}, 'additionalProperties': True}

{'type': 'object', 'properties': {'paragraphs': {'type': 'number', 'description': 'Number of paragraphs to generate (1–10, default: 1)'}, 'words_per_sentence': {'type': 'number', 'description': 'Approximate words per sentence (3–30, default: 10)'}, 'sentences_per_paragraph': {'type': 'number', 'description': 'Sentences per paragraph (1–20, default: 5)'}}}

{'type': 'object', 'properties': {'paragraphs': {}, 'paragraph_count': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['tool_definition'], 'properties': {'tool_definition': {'type': 'object', 'description': 'MCP tool definition object with name, description, inputSchema', 'additionalProperties': True}}}

{'type': 'object', 'properties': {'grade': {}, 'errors': {}, 'warnings': {}, 'error_count': {'type': 'number'}, 'quality_score': {}, 'warning_count': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['url'], 'properties': {'url': {'type': 'string', 'description': 'Base URL of the MCP server (e.g. https://www.ia-qa.com or http://localhost:3001)'}, 'test_tool_name': {'type': 'string', 'description': 'Specific tool name to use in the JSON-RPC test call (defaults to the first tool in the manifest)'}}}

{'type': 'object', 'properties': {'url': {'type': 'string'}, 'score': {'type': 'number'}, 'checks': {'type': 'object'}, 'latency': {'type': 'object'}, 'verdict': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['manifest'], 'properties': {'strict': {'type': 'boolean', 'description': 'Enable strict mode: also check for optional best practices (examples, default values, descriptions > 20 chars)'}, 'manifest': {'type': 'string', 'description': 'MCP server manifest JSON (the response from GET /mcp or tools/list)'}}}

{'type': 'object', 'properties': {'stats': {'type': 'object'}, 'total': {'type': 'number'}, 'checks': {'type': 'array'}, 'failed': {'type': 'number'}, 'passed': {'type': 'number'}, 'verdict': {'type': 'string'}, 'toolIssues': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['base', 'override'], 'properties': {'base': {'type': ['string', 'object', 'array'], 'description': 'The base JSON object (merged into) — a JSON string, or the object itself.'}, 'override': {'type': ['string', 'object', 'array'], 'description': 'The override JSON object (takes precedence) — a JSON string, or the object itself.'}, 'array_strategy': {'enum': ['replace', 'concat', 'unique'], 'type': 'string', 'description': 'Array merge strategy: replace (default), concat, or unique'}}}

{'type': 'object', 'properties': {'merged': {}, 'new_keys': {'type': 'array'}, 'total_keys': {'type': 'number'}, 'overridden_keys': {'type': 'array'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['base', 'variants'], 'properties': {'base': {'type': 'object', 'properties': {'output': {'type': 'string', 'description': 'Required — the answer your system produced for the original question.'}, 'question': {'type': 'string', 'description': 'Optional — the original question, echoed back in the output for readability.'}}, 'description': 'The reference run: the original question and the answer your system produced for it.'}, 'mode': {'enum': ['tfidf', 'embeddings'], 'type': 'string', 'description': 'tfidf (default): free, lexical, deterministic — but a genuine paraphrase rarely reaches 0.80, so gate on case/typo and treat paraphrase as a trend. embeddings: OpenAI text-embedding-3-small, true semantic similarity, requires api_key. translation requires this mode.'}, 'api_key': {'type': 'string', 'description': 'OpenAI API key — required only when mode is embeddings.'}, 'variants': {'type': 'array', 'items': {'type': 'object', 'required': ['relation', 'output'], 'properties': {'id': {'type': 'string', 'description': 'Optional identifier (default: variant_<n>).'}, 'output': {'type': 'string', 'description': 'Required — the answer your system produced for the transformed question.'}, 'question': {'type': 'string', 'description': 'Optional — the transformed question, echoed back for readability.'}, 'relation': {'enum': ['case', 'typo', 'paraphrase', 'reorder', 'translation', 'specialization'], 'type': 'string', 'description': 'Transformation applied to the QUESTION. Decides the metric and the default threshold.'}}}, 'maxItems': 20, 'description': 'Answers produced for transformed versions of the same question, each tagged with the relation that was applied.'}, 'thresholds': {'type': 'object', 'properties': {'case': {'type': 'number', 'maximum': 1, 'minimum': 0}, 'typo': {'type': 'number', 'maximum': 1, 'minimum': 0}, 'reorder': {'type': 'number', 'maximum': 1, 'minimum': 0}, 'paraphrase': {'type': 'number', 'maximum': 1, 'minimum': 0}, 'translation': {'type': 'number', 'maximum': 1, 'minimum': 0}, 'specialization': {'type': 'number', 'maximum': 1, 'minimum': 0}}, 'description': 'Per-relation threshold overrides. Calibrate on your own corpus before gating — the defaults are starting points, not measurements.'}, 'require_all': {'type': 'boolean', 'description': 'If true (default), every gated variant must pass. KEEP THE DEFAULT for any run you gate on. Setting it false is not a tolerance dial but an off switch: relations have asymmetric pass rates (a typo variant usually scores ~1.0 because the answer really is identical), so one trivial row is enough to hold the whole run at PASS while a paraphrase fails. When that happens the result carries an explicit warning naming the failed rows.'}, 'baseline_guard': {'type': 'object', 'properties': {'min_length': {'type': 'number', 'description': 'Minimum base answer length in chars (default 40).'}, 'must_not_match': {'type': 'array', 'items': {'type': 'string'}, 'description': 'Refusal patterns, matched case-insensitively in the FIRST 200 CHARS of the base answer (refusals lead; matching anywhere would flag a long correct answer that merely mentions one). Replaces the FR+EN default list, never merges — pass [] to disable.'}}, 'description': 'Correctness floor applied to the BASE answer before anything is scored. Failing it returns INVALID, not FAIL.'}}}

{'type': 'object', 'properties': {'mode': {'type': 'string'}, 'summary': {'type': 'object'}, 'verdict': {'type': 'string'}, 'weakest': {'type': 'object'}, 'baseline': {'type': 'object'}, 'variants': {'type': 'array', 'items': {'type': 'object'}}, 'warnings': {'type': 'array', 'items': {'type': 'string'}}, 'thresholds': {'type': 'object'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['code'], 'properties': {'code': {'type': 'string', 'description': 'JavaScript code to minify (max 50kb)'}}}

{'type': 'object', 'properties': {'minified': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['schema'], 'properties': {'seed': {'type': 'string', 'description': 'Optional seed string for deterministic output (uses first char codes)'}, 'count': {'type': 'number', 'description': 'Number of mock objects to generate (default: 1, max: 20)'}, 'schema': {'type': ['string', 'object', 'array'], 'description': 'The JSON Schema to generate from — a JSON string, or the schema object itself.'}}}

{'type': 'object', 'properties': {'count': {'type': 'number'}, 'results': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['model'], 'properties': {'model': {'type': 'string', 'description': 'Model name (e.g. "gpt-4o", "claude-3.5-sonnet", "gemini-2.5-pro")'}}}

{'type': 'object', 'properties': {'model': {}, 'pricing_per_1k': {'type': 'object'}}, 'additionalProperties': True}

{'type': 'object', 'properties': {'fid': {'type': 'object', 'description': '[pipeline] {real_images, generated_images} for FID.', 'additionalProperties': True}, 'vqa': {'type': 'object', 'description': '[pipeline] VQA config object (same inputs as vqa_accuracy).', 'additionalProperties': True}, 'clip': {'type': 'object', 'description': '[pipeline] {image_url, text} for CLIP.', 'additionalProperties': True}, 'text': {'type': 'string', 'description': '[clip_score only] Text description to compare against the image.'}, 'model': {'type': 'string', 'description': '[vqa_accuracy] VLM model ID (default: gpt-4o).'}, 'score': {'type': 'number', 'description': '[guide only] Optional score value to interpret.'}, 'action': {'enum': ['guide', 'clip_score', 'fid_score', 'vqa_accuracy', 'pipeline'], 'type': 'string', 'description': 'guide (default) = reference thresholds/interpretation. clip_score/fid_score/vqa_accuracy = compute that metric. pipeline = run all three.'}, 'metric': {'enum': ['clip_score', 'fid', 'vqa_accuracy', 'all'], 'type': 'string', 'description': '[guide only] Metric to explain.'}, 'api_key': {'type': 'string', 'description': '[vqa_accuracy] Your API key for the provider (BYOK).'}, 'image_url': {'type': 'string', 'description': '[clip_score/vqa_accuracy] Public URL of the image.'}, 'test_cases': {'type': 'array', 'items': {'type': 'object', 'properties': {'question': {'type': 'string'}, 'accepted_answers': {'type': 'array', 'items': {'type': 'string'}}}}, 'description': '[vqa_accuracy] Array of {question, accepted_answers} objects.'}, 'real_images': {'type': 'array', 'items': {'type': 'string'}, 'description': '[fid_score] Array of real image URLs.'}, 'image_base64': {'type': 'string', 'description': '[clip_score/vqa_accuracy] Base64-encoded image data.'}, 'system_prompt': {'type': 'string', 'description': '[vqa_accuracy] Optional system prompt.'}, 'image_mime_type': {'type': 'string', 'description': '[clip_score/vqa_accuracy] MIME type for base64 image.'}, 'generated_images': {'type': 'array', 'items': {'type': 'string'}, 'description': '[fid_score] Array of generated image URLs.'}}}

{'type': 'object', 'properties': {'errors': {}, 'metrics': {}, 'results': {}, 'web_tool': {'type': 'string'}, 'best_practices': {'type': 'array'}, 'comparison_table': {'type': 'array'}, 'score_interpretation': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['needle', 'question'], 'properties': {'needle': {'type': 'string', 'description': 'The fact to hide (e.g. "The secret code is ALPHA-42")'}, 'tokens': {'type': 'integer', 'default': 5000, 'description': 'Target haystack size in tokens (default: 5000, max: 100000)'}, 'position': {'enum': ['start', 'middle', 'end', 'random'], 'type': 'string', 'default': 'middle', 'description': 'Where to insert the needle: "start", "middle", "end", "random" (default: "middle")'}, 'question': {'type': 'string', 'description': 'The question to ask the LLM (e.g. "What is the secret code?")'}}}

{'type': 'object', 'properties': {'needle': {}, 'haystack': {}, 'position': {}, 'question': {}, 'insert_block': {}, 'total_blocks': {'type': 'number'}, 'estimated_tokens': {}}, 'additionalProperties': True}

{'type': 'object', 'properties': {'batch': {'type': 'array', 'items': {'type': 'array', 'items': {'type': 'number'}}, 'description': 'Batch of vectors to normalize (overrides vector)'}, 'vector': {'type': 'array', 'items': {'type': 'number'}, 'description': 'Single vector to normalize'}}}

{'type': 'object', 'properties': {'mode': {'type': 'string'}, 'norm': {'type': 'number'}, 'count': {'type': 'number'}, 'index': {}, 'vector': {}, 'results': {}, 'dimension': {'type': 'number'}, 'norm_after': {'type': 'number'}, 'normalized': {}, 'norm_before': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'Text to normalize'}, 'trim_file': {'type': 'boolean', 'description': 'Trim leading/trailing blank lines (default: true)'}, 'trim_lines': {'type': 'boolean', 'description': 'Trim trailing whitespace from each line (default: true)'}, 'line_ending': {'type': 'string', 'description': '"lf" (default), "crlf", or "cr"'}, 'tab_to_spaces': {'type': 'number', 'description': 'Convert tabs to N spaces (omit to keep tabs)'}, 'collapse_blanks': {'type': 'boolean', 'description': 'Collapse runs of blank lines down to max_blank_lines (default: true)'}, 'max_blank_lines': {'type': 'number', 'description': 'Blank lines to keep when collapsing, 0-10 (default: 2)'}}}

{'type': 'object', 'properties': {'result': {}, 'line_ending': {}, 'original_length': {'type': 'number'}, 'normalized_length': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'Number to convert (e.g., "255", "0xFF", "0b1010", "0o77")'}, 'to_base': {'type': 'number', 'description': 'Target base 2–36 (omit to get all common bases)'}, 'from_base': {'type': 'number', 'description': 'Source base 2–36 (auto-detects prefix if omitted)'}}}

{'type': 'object', 'properties': {'octal': {'type': 'string'}, 'binary': {'type': 'string'}, 'result': {'type': 'string'}, 'decimal': {}, 'to_base': {}, 'from_base': {}, 'hexadecimal': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': ['string', 'object', 'array'], 'description': 'The OpenAPI 3.x spec — a JSON string, a YAML string, or the already-parsed spec object.'}}}

{'type': 'object', 'properties': {'score': {'type': 'number'}, 'stats': {'type': 'object'}, 'errors': {}, 'verdict': {}, 'warnings': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['text'], 'properties': {'text': {'type': 'string', 'description': 'The prompt text to optimize'}, 'options': {'type': 'object', 'properties': {'fillers': {'type': 'boolean', 'default': True}, 'duplicates': {'type': 'boolean', 'default': True}, 'whitespace': {'type': 'boolean', 'default': True}, 'instructions': {'type': 'boolean', 'default': True}}, 'description': 'Toggle optimization steps (all true by default)'}}}

{'type': 'object', 'properties': {'steps': {}, 'optimized': {}, 'tokens_after': {}, 'tokens_saved': {}, 'percent_saved': {'type': 'string'}, 'tokens_before': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'CSV content to parse'}, 'header': {'type': 'boolean', 'description': 'Treat the first row as headers (default: true)'}, 'delimiter': {'type': 'string', 'description': 'Field delimiter character (default: ",")'}}}

{'type': 'object', 'properties': {'rows': {'type': 'array'}, 'columns': {'type': 'number'}, 'headers': {'type': 'array'}, 'row_count': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['headers'], 'properties': {'headers': {'type': 'string', 'description': 'Raw HTTP headers (one "Name: Value" per line)'}, 'analyze_security': {'type': 'boolean', 'description': 'Audit for missing security headers (default: true)'}}}

{'type': 'object', 'properties': {'parsed': {'type': 'object'}, 'security': {'type': 'object'}, 'header_count': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['issue_key', 'jira_base_url', 'jira_email', 'jira_token', 'test_suite'], 'properties': {'issue_key': {'type': 'string', 'description': 'Jira issue key, e.g. "PROJ-123"'}, 'jira_email': {'type': 'string', 'description': 'Atlassian account email'}, 'jira_token': {'type': 'string', 'description': 'Atlassian API token'}, 'test_suite': {'type': 'object', 'description': 'The test_suite object from jira_to_test_suite result', 'additionalProperties': True}, 'jira_base_url': {'type': 'string', 'description': 'Atlassian base URL'}}}

{'type': 'object', 'properties': {'success': {'type': 'boolean'}, 'comment_id': {'type': 'string'}, 'comment_url': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['diff', 'commit_message'], 'properties': {'diff': {'type': 'string', 'description': 'Unified git diff (output of `git diff HEAD`)'}, 'context': {'type': 'string', 'description': 'Optional: PR title or description for richer bug analysis'}, 'commit_message': {'type': 'string', 'description': 'The commit message to lint (e.g. "feat(auth): add OAuth2 login")'}}}

{'type': 'object', 'properties': {'flags': {'type': 'array', 'items': {'type': 'string'}}, 'score': {'type': 'number'}, 'checks': {'type': 'object'}, 'verdict': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'The user input or prompt to scan for injection patterns'}, 'sensitivity': {'enum': ['low', 'medium', 'high'], 'type': 'string', 'description': 'Detection sensitivity (default: medium)'}}}

{'type': 'object', 'properties': {'notes': {}, 'detections': {}, 'risk_level': {}, 'sensitivity': {}, 'input_length': {'type': 'number'}, 'detections_count': {'type': 'number'}, 'quoted_detections': {'type': 'number'}, 'injection_detected': {'type': 'boolean'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['template'], 'properties': {'strict': {'type': 'boolean', 'description': 'Throw error if any variable is not provided (default: false)'}, 'template': {'type': 'string', 'description': 'Prompt template with {{variable}} placeholders'}, 'variables': {'type': 'object', 'description': 'Key-value pairs to fill (e.g. {"name":"Alice","role":"engineer"})', 'additionalProperties': True}}}

{'type': 'object', 'properties': {'result': {}, 'total_vars': {}, 'filled_variables': {}, 'unfilled_variables': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['system_prompt', 'user_prompt'], 'properties': {'max_tokens': {'type': 'number', 'description': 'Max token budget for the test'}, 'temperature': {'type': 'number', 'description': 'Temperature to use'}, 'user_prompt': {'type': 'string', 'description': 'The user prompt to send'}, 'check_safety': {'type': 'boolean', 'description': 'Include safety/PII checks in the rubric'}, 'must_include': {'type': 'string', 'description': 'Required content (comma-separated)'}, 'system_prompt': {'type': 'string', 'description': 'The system prompt under test'}, 'expected_format': {'enum': ['json', 'markdown', 'code', 'plain', 'any'], 'type': 'string', 'description': 'Expected output format'}, 'must_not_include': {'type': 'string', 'description': 'Forbidden content (comma-separated)'}, 'expected_behavior': {'type': 'string', 'description': 'Description of what the LLM should do (free text)'}, 'adversarial_prompts': {'type': 'boolean', 'description': 'Auto-generate adversarial test variants (jailbreak, injection, edge cases)'}}}

{'type': 'object', 'properties': {'rubric': {}, 'categories': {'type': 'array'}, 'total_tests': {'type': 'number'}, 'instructions': {'type': 'string'}, 'test_suite_name': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['query', 'chunks'], 'properties': {'query': {'type': 'string', 'description': 'The user query'}, 'top_k': {'type': 'number', 'description': 'Return top K results (default: all)'}, 'chunks': {'type': 'array', 'items': {'type': 'string'}, 'description': 'Array of text chunks to rank'}}}

{'type': 'object', 'properties': {'rank': {'type': 'number'}, 'index': {}, 'query': {}, 'score': {'type': 'string'}, 'results': {}, 'returned': {'type': 'number'}, 'total_chunks': {'type': 'number'}, 'chunk_preview': {}, 'keyword_overlap': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['tool_name', 'score'], 'properties': {'score': {'type': 'number', 'maximum': 5, 'minimum': 1, 'description': 'Rating from 1 (poor) to 5 (excellent)'}, 'comment': {'type': 'string', 'description': 'Strongly encouraged — explain what you were trying to do and whether the tool got you there. Be specific about what was missing, wrong, or a poor fit. This is the most valuable part of the rating. Up to 2000 chars are stored; go over and the response says so (truncated: true) — send the remainder as a second call rather than assuming it landed.'}, 'tool_name': {'type': 'string', 'description': 'Name of the MCP tool to rate (e.g. "format_json", "shield_analyze")'}}}

{'type': 'object', 'properties': {'ok': {'type': 'boolean'}, 'score': {}, 'comment': {}, 'message': {'type': 'string'}, 'rated_at': {'type': 'string'}, 'tool_name': {}, 'truncated': {'type': 'boolean'}, 'stored_chars': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'Text to redact PII from'}, 'types': {'type': 'string', 'description': 'Comma-separated types to redact (default: all). Options: email, phone, ssn, credit_card, ip_address, jwt'}, 'marker': {'type': 'string', 'description': 'Custom replacement marker (default: "REDACTED"). Result: [REDACTED_EMAIL]'}}}

{'type': 'object', 'properties': {'clean': {'type': 'boolean'}, 'pii_found': {}, 'replacements': {}, 'redacted_text': {}, 'total_redactions': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['pattern', 'input'], 'properties': {'flags': {'type': 'string', 'description': 'Regex flags: g (global), i (case-insensitive), m (multiline), s (dotAll) — default: ""'}, 'input': {'type': 'string', 'description': 'The string to test against (max 50 KB)'}, 'pattern': {'type': 'string', 'description': 'Regular expression pattern (without delimiters)'}}}

{'type': 'object', 'properties': {'note': {}, 'flags': {}, 'matched': {}, 'matches': {}, 'pattern': {}, 'verdict': {}, 'elapsed_ms': {'type': 'number'}, 'match_count': {'type': 'number'}, 'redos_detected': {'type': 'boolean'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['query', 'passages'], 'properties': {'query': {'type': 'string', 'description': 'The search query or question to rank against'}, 'top_k': {'type': 'integer', 'maximum': 10, 'minimum': 1, 'description': 'k for Precision@k evaluation (default 3)'}, 'api_key': {'type': 'string', 'description': 'Your NVIDIA API key (BYOK), used only when no passage carries a score. Transits RAM for the single call, never stored.'}, 'passages': {'type': 'array', 'items': {'type': 'object', 'required': ['text'], 'properties': {'id': {'type': 'string'}, 'text': {'type': 'string'}, 'score': {'type': 'number', 'description': 'Relevance score from YOUR reranker. Present on every passage → ranking is done from these (offline, no key). Higher = more relevant. Score all passages or none.'}, 'relevant': {'type': 'boolean', 'description': 'Ground truth: is this passage relevant?'}}}, 'description': 'Array of passage objects to rank (min 2, max 20)'}, 'threshold': {'type': 'number', 'maximum': 1, 'minimum': 0, 'description': 'Minimum Precision@k to PASS (0-1, default 0.5)'}}}

{'type': 'object', 'properties': {'k': {'type': 'number'}, 'mode': {'type': 'string'}, 'model': {'type': 'string'}, 'ranked': {'type': 'array', 'items': {'type': 'object'}}, 'verdict': {'type': 'string'}, 'threshold': {'type': 'number'}, 'latency_ms': {'type': 'number'}, 'recall_at_k': {'type': 'number'}, 'precision_at_k': {'type': 'number'}, 'total_passages': {'type': 'number'}, 'has_ground_truth': {'type': 'boolean'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['question', 'response'], 'properties': {'question': {'type': 'string', 'description': 'The original question/prompt'}, 'response': {'type': 'string', 'description': 'The LLM response to score'}, 'max_length': {'type': 'number', 'description': 'Maximum character length. Scored as a proportional penalty beyond it.'}, 'expected_keywords': {'type': 'array', 'items': {'type': 'string'}, 'description': 'Keywords a correct answer must contain (case-insensitive). Scored as coverage.'}}}

{'type': 'object', 'properties': {'grade': {}, 'stats': {'type': 'object'}, 'reason': {'type': 'string'}, 'signals': {'type': 'object'}, 'breakdown': {'type': 'object'}, 'max_score': {'type': 'number'}, 'total_score': {}, 'not_measured': {'type': 'array'}}, 'additionalProperties': True}

{'type': 'object', 'properties': {'api_keys': {'type': 'object', 'properties': {'hf': {'type': 'string'}, 'groq': {'type': 'string'}, 'google': {'type': 'string'}, 'openai': {'type': 'string'}, 'anthropic': {'type': 'string'}}, 'description': 'API keys to use for LLM generation (all optional — falls back to server env vars)'}, 'overrides': {'type': 'object', 'properties': {'model': {'type': 'string'}, 'provider': {'type': 'string'}, 'temperature': {'type': 'number'}, 'system_prompt': {'type': 'string'}}, 'description': 'Override contract defaults'}, 'contract_path': {'type': 'string', 'description': 'Absolute or relative path to a .ia-eval.yaml file (required unless inline_contract is provided)'}, 'inline_contract': {'type': 'object', 'description': 'Raw contract object (alternative to contract_path). Must contain top-level "metadata" ({name, version, model?, provider?}), "expectations" ({min_score?}), and "scenarios" ([{id, input, ground_truth?}]) — scenarios alone are rejected. Use generate_eval_yaml to scaffold one.', 'additionalProperties': True}}}

{'type': 'object', 'properties': {'summary': {'type': 'object'}, 'metadata': {'type': 'object'}, 'warnings': {}, 'contract_path': {}, 'scenario_results': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['git_diff'], 'properties': {'context': {'type': 'string', 'description': 'Optional PR title or description for richer analysis'}, 'git_diff': {'type': 'string', 'description': 'Unified git diff (output of `git diff HEAD` or copied from GitHub diff view)'}}}

{'type': 'object', 'properties': {'sla': {}, 'high': {}, 'topBugs': {'type': 'array'}, 'critical': {}, 'bugsFound': {'type': 'number'}, 'riskLevel': {}, 'riskScore': {}, 'disclaimer': {'type': 'string'}, 'impactAreas': {'type': 'array'}, 'inputFormat': {'type': 'string'}, 'notAnalysed': {'type': 'array'}, 'riskFactors': {'type': 'array'}, 'changedFiles': {}, 'severityLevel': {}, 'testCasesGenerated': {}, 'mergeRecommendation': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['cases'], 'properties': {'mode': {'enum': ['tfidf', 'embeddings'], 'type': 'string', 'description': 'tfidf (default): fast, free, lexical. embeddings: OpenAI text-embedding-3-small, true semantic similarity, requires api_key.'}, 'cases': {'type': 'array', 'items': {'type': 'object', 'required': ['actual', 'expected'], 'properties': {'id': {'type': 'string', 'description': 'Optional identifier for this case.'}, 'actual': {'type': 'string', 'description': 'The text produced by your LLM/system.'}, 'expected': {'type': 'string', 'description': 'The reference/ground-truth text.'}}}, 'maxItems': 50, 'description': 'Array of (actual, expected) pairs to evaluate.'}, 'api_key': {'type': 'string', 'description': 'OpenAI API key — required only when mode is embeddings.'}, 'thresholds': {'type': 'object', 'properties': {'cosine': {'type': 'number', 'maximum': 1, 'minimum': 0, 'description': 'Minimum cosine similarity to pass (default: 0.75).'}, 'rouge_l': {'type': 'number', 'maximum': 1, 'minimum': 0, 'description': 'Minimum ROUGE-L F1 to pass (default: 0.5).'}}, 'description': 'Pass/fail thresholds (defaults: cosine 0.75, rouge_l 0.5).'}, 'require_all': {'type': 'boolean', 'description': 'If true (default), all cases must pass for overall PASS. If false, at least one case passing returns PASS.'}}}

{'type': 'object', 'properties': {'mode': {'type': 'string'}, 'total': {'type': 'number'}, 'failed': {'type': 'number'}, 'passed': {'type': 'number'}, 'results': {'type': 'array', 'items': {'type': 'object'}}, 'verdict': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['test_cases', 'model', 'api_key'], 'properties': {'model': {'enum': ['gpt-4o', 'gpt-4o-mini', 'claude-3-5-sonnet-20241022', 'claude-3-5-haiku-20241022', 'gemini-1.5-flash', 'gemini-2.0-flash'], 'type': 'string', 'description': 'VLM model to use.'}, 'api_key': {'type': 'string', 'description': 'API key for the model provider (OpenAI sk-, Anthropic sk-ant-, or Google AIzaSy...).'}, 'image_url': {'type': 'string', 'description': 'Public URL of the image to evaluate (required unless image_base64 is provided).'}, 'threshold': {'type': 'number', 'description': 'Pass rate threshold for overall verdict (default: 80, 0–100).'}, 'test_cases': {'type': 'array', 'items': {'type': 'object', 'required': ['question'], 'properties': {'id': {'type': 'string', 'description': 'Optional identifier for this case.'}, 'question': {'type': 'string', 'description': 'Question to ask the VLM about the image.'}, 'assertion_type': {'enum': ['contains', 'not_contains', 'json_format', 'min_length', 'max_length', 'semantic_contains'], 'type': 'string', 'description': 'Assertion to run on the VLM response. semantic_contains uses TF-IDF cosine similarity ≥ 0.4.'}, 'assertion_value': {'type': 'string', 'description': 'Expected value for the assertion (not needed for json_format).'}}}, 'maxItems': 10, 'description': 'Array of test cases to run.'}, 'image_base64': {'type': 'string', 'description': 'Base64-encoded image data (required unless image_url is provided).'}, 'system_prompt': {'type': 'string', 'description': 'Optional system prompt sent to the VLM.'}, 'image_mime_type': {'type': 'string', 'description': 'MIME type of the image if using image_base64 (default: image/jpeg).'}}}

{'type': 'object', 'properties': {'model': {'type': 'string'}, 'total': {'type': 'number'}, 'failed': {'type': 'number'}, 'passed': {'type': 'number'}, 'results': {'type': 'array', 'items': {'type': 'object'}}, 'verdict': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['test_cases', 'models', 'api_keys'], 'properties': {'models': {'type': 'array', 'items': {'enum': ['gpt-4o', 'gpt-4o-mini', 'claude-3-5-sonnet-20241022', 'claude-3-5-haiku-20241022', 'gemini-1.5-flash', 'gemini-2.0-flash'], 'type': 'string'}, 'maxItems': 6, 'minItems': 1, 'description': 'Array of model IDs to compare (runs in parallel).'}, 'api_keys': {'type': 'object', 'description': 'Map of model ID → API key. Example: { "gpt-4o": "sk-...", "claude-3-5-sonnet-20241022": "sk-ant-..." }', 'additionalProperties': {'type': 'string'}}, 'image_url': {'type': 'string', 'description': 'Public URL of the image to evaluate (required unless image_base64 is provided).'}, 'threshold': {'type': 'number', 'description': 'Pass rate threshold for overall verdict (default: 80, 0–100).'}, 'test_cases': {'type': 'array', 'items': {'type': 'object', 'required': ['question'], 'properties': {'id': {'type': 'string', 'description': 'Optional identifier for this case.'}, 'question': {'type': 'string', 'description': 'Question to ask the VLM about the image.'}, 'assertion_type': {'enum': ['contains', 'not_contains', 'json_format', 'min_length', 'max_length', 'semantic_contains'], 'type': 'string', 'description': 'Assertion to run on the VLM response.'}, 'assertion_value': {'type': 'string', 'description': 'Expected value for the assertion (not needed for json_format).'}}}, 'maxItems': 10, 'description': 'Array of test cases to run against every model.'}, 'image_base64': {'type': 'string', 'description': 'Base64-encoded image data (required unless image_url is provided).'}, 'system_prompt': {'type': 'string', 'description': 'Optional system prompt sent to every VLM.'}, 'image_mime_type': {'type': 'string', 'description': 'MIME type of the image if using image_base64 (default: image/jpeg).'}}}

{'type': 'object', 'properties': {'suites': {'type': 'array', 'items': {'type': 'object'}}, 'verdict': {'type': 'string'}, 'total_failed': {'type': 'number'}, 'total_passed': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'properties': {'scenario': {'type': 'string', 'description': 'Scenario id. Omit to list every available scenario with its expected verdict. Ids: no-change, swap-label, add-testid, duplicate-role-name, remove-element, insert-sibling, rename-label, counter-label, move-behind-menu, add-element'}, 'include_html': {'type': 'boolean', 'description': 'Include the generated HTML of the mutated page (default false). Only useful if you want to render or re-capture it yourself; the loop does not need it.'}}}

{'type': 'object', 'properties': {'html': {}, 'page': {}, 'blurb': {}, 'count': {'type': 'number'}, 'title': {}, 'current': {'type': 'object'}, 'teaches': {}, 'baseline': {'type': 'object'}, 'expected': {'type': 'object'}, 'scenario': {}, 'mutations': {'type': 'array'}, 'scenarios': {'type': 'array'}, 'how_to_run_the_loop': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['head_html'], 'properties': {'head_html': {'type': 'string', 'description': 'Raw HTML of the <head> section (or full page HTML) to analyze'}}}

{'type': 'object', 'properties': {'grade': {}, 'score': {}, 'checks': {}, 'passed': {'type': 'number'}, 'max_score': {'type': 'number'}, 'total_checks': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['jql', 'jira_base_url', 'jira_email', 'jira_token'], 'properties': {'jql': {'type': 'string', 'description': 'JQL query string, e.g. "project = PROJ AND status = Open AND assignee = currentUser() ORDER BY priority DESC"'}, 'fields': {'type': 'array', 'items': {'type': 'string'}, 'description': 'Fields per issue. Default: summary, status, assignee, priority, issuetype, labels, created, updated'}, 'jira_email': {'type': 'string', 'description': 'Atlassian account email'}, 'jira_token': {'type': 'string', 'description': 'Atlassian API token'}, 'max_results': {'type': 'number', 'description': 'Max issues to return (default: 10, max: 50)'}, 'jira_base_url': {'type': 'string', 'description': 'Atlassian base URL, e.g. "https://mycompany.atlassian.net"'}}}

{'type': 'object', 'properties': {'jql': {'type': 'string'}, 'total': {'type': 'number'}, 'issues': {'type': 'array', 'items': {'type': 'object'}}, 'returned': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'Text or code to scan for secrets'}, 'types': {'type': 'string', 'description': 'Comma-separated families to scan (default: all): aws, gcp, azure, openai, anthropic, huggingface, github, gitlab, stripe, slack, twilio, sendgrid, jwt, private_key, connection_string, bearer, basic_auth, generic. Individual pattern names (e.g. "aws_access_key", "github_fine") are also accepted. An unknown value is rejected with an error — a scoped scan never silently returns "clean".'}}}

{'type': 'object', 'properties': {'summary': {'type': 'string'}, 'findings': {}, 'risk_level': {}, 'input_lines': {'type': 'number'}, 'scanned_types': {}, 'secrets_found': {}, 'findings_count': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'properties': {'url': {'type': 'string', 'description': 'Optional. Full public URL to check (e.g. https://example.com). Omit it entirely when using `headers`. The server cannot reach localhost/private IPs.'}, 'headers': {'description': 'Optional, and sufficient on its own (no url needed). The response headers to grade, either as an object {"strict-transport-security": "max-age=...", ...} or as the raw header block pasted as a string (e.g. `curl -sI` output). Use this to audit a local server the remote MCP cannot reach.'}}}

{'type': 'object', 'properties': {'fix': {}, 'key': {}, 'url': {}, 'weak': {}, 'grade': {}, 'score': {}, 'value': {}, 'header': {}, 'source': {}, 'weight': {}, 'details': {}, 'missing': {}, 'weak_count': {'type': 'number'}, 'missing_count': {'type': 'number'}, 'overall_grade': {}, 'headers_checked': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['response'], 'properties': {'model': {'type': 'string', 'description': 'LLM model for AI-powered deep analysis (default: "openai/gpt-oss-20b"). Set to "none" to skip LLM check. Supports any model from list_llm_models.'}, 'rules': {'type': 'array', 'items': {'type': 'object', 'properties': {'type': {'type': 'string'}, 'label': {'type': 'string'}, 'value': {'type': 'string'}}}, 'description': 'Optional guardrail rules array (same format as guardrail_test tool)'}, 'prompt': {'type': 'string', 'description': 'Optional original prompt. Used for quality scoring AND scanned for prompt injection in its own right (checks.injection_prompt) — pass it whenever you have it, it is where the attack actually lands.'}, 'source': {'type': 'string', 'description': 'Optional reference/source text for hallucination grounding check'}, 'response': {'type': 'string', 'description': 'The LLM-generated response to analyze'}}}

{'type': 'object', 'properties': {'flags': {}, 'grade': {}, 'score': {}, 'checks': {'type': 'object'}, 'verdict': {}}, 'additionalProperties': True}

{'type': 'object', 'properties': {'batch': {'type': 'array', 'items': {'type': 'object', 'required': ['reference', 'hypothesis'], 'properties': {'reference': {'type': 'string'}, 'hypothesis': {'type': 'string'}}}, 'description': 'Batch mode: array of {reference, hypothesis} pairs.'}, 'metrics': {'type': 'array', 'items': {'type': 'string'}, 'description': 'Metrics to compute (default: all). Options: "cosine_bow", "cosine_tfidf", "jaccard", "rouge1", "rouge2", "rougeL", "bleu"'}, 'reference': {'type': 'string', 'description': 'Reference / expected text (ground truth)'}, 'threshold': {'type': 'number', 'description': 'Optional pass/fail threshold (0-1). Applies to ROUGE-L F1 score.'}, 'hypothesis': {'type': 'string', 'description': 'Hypothesis / actual text (LLM output)'}}}

{'type': 'object', 'properties': {'f1': {'type': 'number'}, 'mode': {'type': 'string'}, 'count': {'type': 'number'}, 'recall': {'type': 'number'}, 'results': {}, 'precision': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'trim': {'type': 'boolean', 'description': 'Trim whitespace from each line (default: true)'}, 'input': {'type': 'string', 'description': 'Multi-line text to process'}, 'filter': {'type': 'string', 'description': 'For "filter": keep lines containing this substring (case-insensitive)'}, 'operation': {'type': 'string', 'description': '"sort" (default), "sort_desc", "reverse", "deduplicate", "unique_sort", "filter"'}, 'remove_empty': {'type': 'boolean', 'description': 'Remove empty lines (default: true)'}}}

{'type': 'object', 'properties': {'result': {'type': 'string'}, 'removed': {'type': 'number'}, 'line_count': {'type': 'number'}, 'original_count': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input', 'chunk_tokens'], 'properties': {'input': {'type': 'string', 'description': 'Text to split into chunks'}, 'overlap': {'type': 'number', 'description': 'Token overlap between consecutive chunks (default: 0)'}, 'chunk_tokens': {'type': 'number', 'description': 'Maximum tokens per chunk (10–8000)'}}}

{'type': 'object', 'properties': {'chunks': {'type': 'array'}, 'chunk_count': {'type': 'number'}, 'overlap_tokens': {}, 'tokens_per_chunk': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['host'], 'properties': {'host': {'type': 'string', 'description': 'Hostname to check (e.g. example.com). Do not include https:// prefix.'}, 'port': {'type': 'number', 'description': 'Port number (default: 443)'}}}

{'type': 'object', 'properties': {'host': {'type': 'string'}, 'grade': {'type': 'string'}, 'cipher': {'type': 'object'}, 'issuer': {'type': 'object'}, 'issues': {'type': 'array', 'items': {'type': 'string'}}, 'subject': {'type': 'object'}, 'protocol': {'type': 'string'}, 'valid_to': {'type': 'string'}, 'is_expired': {'type': 'boolean'}, 'valid_from': {'type': 'string'}, 'is_self_signed': {'type': 'boolean'}, 'days_until_expiry': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'Markdown text to convert to plain text'}}}

{'type': 'object', 'properties': {'text': {}, 'original_length': {'type': 'number'}, 'stripped_length': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['role'], 'properties': {'role': {'type': 'string', 'description': 'Role/persona (e.g. "Senior QA Engineer", "JSON extraction assistant")'}, 'task': {'type': 'string', 'description': 'Main task or objective'}, 'tone': {'enum': ['professional', 'friendly', 'concise', 'technical', 'educational'], 'type': 'string', 'description': 'Communication tone'}, 'examples': {'type': 'string', 'description': 'Brief examples to include'}, 'language': {'type': 'string', 'description': 'Response language (e.g. "French")'}, 'constraints': {'type': 'array', 'items': {'type': 'string'}, 'description': 'Rules and constraints to follow'}, 'output_format': {'type': 'string', 'description': 'Expected output format description'}}}

{'type': 'object', 'properties': {'sections': {'type': 'object'}, 'system_prompt': {}, 'token_estimate': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['skill_md'], 'properties': {'model': {'type': 'string', 'description': 'LLM model ID to use for both scenario generation and testing (e.g. gpt-4o-mini, claude-3-5-haiku-20241022). Defaults to openai/gpt-oss-20b (Groq, server key).'}, 'api_key': {'type': 'string', 'description': 'API key for the chosen model provider. Not required when using the default Groq model.'}, 'skill_md': {'type': 'string', 'description': 'Full content of the SKILL.md file to test. Must include a name, a "Use when:" trigger description, and at least one step.'}, 'scenario_count': {'enum': [4, 6, 8, 10], 'type': 'number', 'description': 'Number of test scenarios to generate: half trigger-positive, half trigger-negative. Default: 6.'}}}

{'type': 'object', 'properties': {'score': {'type': 'number'}, 'verdict': {'type': 'string'}, 'scenarios': {'type': 'array', 'items': {'type': 'object'}}, 'step_adherence': {'type': 'number'}, 'trigger_accuracy': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'The text to analyse'}}}

{'type': 'object', 'properties': {'chars': {}, 'lines': {}, 'words': {}, 'sentences': {}, 'paragraphs': {}, 'chars_no_space': {}, 'reading_time_minutes': {}}, 'additionalProperties': True}

{'type': 'object', 'properties': {'input': {'description': 'Unix timestamp (number, seconds or ms) or ISO date string. Omit to get the current time.'}}}

{'type': 'object', 'properties': {'iso': {'type': 'string'}, 'utc': {'type': 'string'}, 'date': {'type': 'string'}, 'time': {'type': 'string'}, 'unix_s': {'type': 'number'}, 'unix_ms': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['model'], 'properties': {'model': {'type': 'string', 'description': 'Model name (e.g. gpt-4o, claude-3.5-sonnet, gemini-2.0-flash)'}, 'context': {'type': 'string', 'description': 'Actual context text (will estimate tokens)'}, 'user_input': {'type': 'string', 'description': 'Actual user input text (will estimate tokens)'}, 'system_prompt': {'type': 'string', 'description': 'Actual system prompt text (will estimate tokens)'}, 'context_tokens': {'type': 'number', 'description': 'Token count for RAG context / documents'}, 'user_input_tokens': {'type': 'number', 'description': 'Token count for user message'}, 'system_prompt_tokens': {'type': 'number', 'description': 'Token count for system prompt'}, 'expected_output_tokens': {'type': 'number', 'description': 'Expected max output tokens'}}}

{'type': 'object', 'properties': {'model': {}, 'warnings': {}, 'breakdown': {'type': 'object'}, 'context_window': {}, 'fits_in_window': {}, 'remaining_tokens': {}, 'utilization_percent': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['text'], 'properties': {'text': {'type': 'string', 'description': 'Text to scan'}, 'categories': {'type': 'array', 'items': {'enum': ['profanity', 'hate_speech', 'violence', 'sexual', 'self_harm', 'bias'], 'type': 'string'}, 'description': 'Categories to check (default: all)'}}}

{'type': 'object', 'properties': {'method': {'type': 'string'}, 'results': {}, 'text_length': {'type': 'number'}, 'overall_risk': {}, 'categories_checked': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input', 'operation'], 'properties': {'n': {'type': 'number', 'description': 'For first_n / last_n: number of items'}, 'path': {'type': 'string', 'description': 'Optional dot-notation path to the array within the JSON object (e.g. "data.items")'}, 'field': {'type': 'string', 'description': 'Field to operate on (for sort_by, group_by, count_by, uniq_by, filter)'}, 'input': {'type': ['string', 'object', 'array'], 'description': 'The JSON containing an array (or an object with an array at `path`) — a JSON string, or the value itself.'}, 'fields': {'type': 'string', 'description': 'Comma-separated field list for "pluck" (e.g. "id,name,email")'}, 'filter_op': {'type': 'string', 'description': 'For "filter": "==" | "!=" | ">" | ">=" | "<" | "<=" | "contains" | "exists" | "!exists"'}, 'operation': {'type': 'string', 'description': 'Operation: "pluck", "filter", "sort_by", "group_by", "count_by", "uniq_by", "reverse", "first_n", "last_n", "flatten"'}, 'sort_order': {'type': 'string', 'description': 'For sort_by: "asc" (default) or "desc"'}, 'filter_value': {'type': 'string', 'description': 'For "filter": value to compare against'}}}

{'type': 'object', 'properties': {'count': {'type': 'number'}, 'field': {}, 'order': {}, 'total': {'type': 'number'}, 'fields': {}, 'result': {}, 'removed': {'type': 'number'}, 'operation': {'type': 'string'}, 'group_count': {'type': 'number'}, 'unique_values': {'type': 'number'}, 'removed_duplicates': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input', 'max_tokens'], 'properties': {'input': {'type': 'string', 'description': 'Text to truncate'}, 'from_end': {'type': 'boolean', 'description': 'Keep the end of the text instead of the start (default: false)'}, 'max_tokens': {'type': 'number', 'description': 'Maximum number of tokens to keep'}}}

{'type': 'object', 'properties': {'text': {}, 'truncated': {'type': 'boolean'}, 'tokens_estimate': {}, 'original_tokens_estimate': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'HTML-encoded string to unescape'}}}

{'type': 'object', 'properties': {'unescaped': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'URL-encoded string to decode'}}}

{'type': 'object', 'properties': {'decoded': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'mode': {'type': 'string', 'description': '"component" (default) or "full" for encodeURI behavior'}, 'input': {'type': 'string', 'description': 'String to URL-encode'}}}

{'type': 'object', 'properties': {'encoded': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['trace', 'assertions'], 'properties': {'trace': {'oneOf': [{'type': 'string'}, {'type': 'object', 'additionalProperties': True}, {'type': 'array', 'items': {}}], 'description': 'Agent execution trace as JSON (OpenAI messages array, LangChain run tree) or plain text log (Thought/Action/Observation format).'}, 'format': {'enum': ['auto', 'openai', 'langchain'], 'type': 'string', 'description': 'Trace format. auto (default) detects automatically.'}, 'assertions': {'type': 'array', 'items': {'type': 'object', 'required': ['type'], 'properties': {'id': {'type': 'string', 'description': 'Optional assertion identifier.'}, 'max': {'type': 'number', 'description': '[max_calls] Maximum number of allowed calls.'}, 'min': {'type': 'number', 'description': '[min_calls] Minimum number of required calls.'}, 'tool': {'type': 'string', 'description': 'Tool name to check (for must_call, must_not_call, max_calls, min_calls).'}, 'type': {'enum': ['order', 'must_call', 'must_not_call', 'max_calls', 'min_calls', 'no_error', 'recovery'], 'type': 'string', 'description': 'Assertion type.'}, 'after': {'type': 'string', 'description': '[order] Tool that must be called after.'}, 'before': {'type': 'string', 'description': '[order] Tool that must be called first.'}}}, 'maxItems': 30, 'description': 'List of assertions to validate against the trace.'}}}

{'type': 'object', 'properties': {'steps': {'type': 'array', 'items': {'type': 'object'}}, 'results': {'type': 'array', 'items': {'type': 'object'}}, 'summary': {'type': 'object', 'additionalProperties': True}, 'verdict': {'type': 'string'}, 'warnings': {'type': 'array', 'items': {'type': 'string'}}}, 'additionalProperties': True}

{'type': 'object', 'required': ['email'], 'properties': {'email': {'type': 'string', 'description': 'Email address to validate'}}}

{'type': 'object', 'properties': {'email': {}, 'valid': {'type': 'boolean'}, 'reason': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['response'], 'properties': {'response': {'type': 'string', 'description': 'The MCP tool result as a JSON string to validate'}, 'min_items': {'type': 'number', 'description': 'If response is an array, minimum number of items expected'}, 'expected_type': {'enum': ['object', 'array', 'string', 'number'], 'type': 'string', 'description': 'Expected top-level type: "object", "array", "string", "number"'}, 'required_keys': {'type': 'string', 'description': 'Comma-separated list of keys that MUST exist in the response (dot-notation for nested: "data.id, data.name")'}, 'actual_latency': {'type': 'number', 'description': 'Actual measured latency in ms (from the call)'}, 'forbidden_keys': {'type': 'string', 'description': 'Comma-separated list of keys that MUST NOT exist (e.g. "password, secret, token")'}, 'max_size_bytes': {'type': 'number', 'description': 'Maximum acceptable response size in bytes'}, 'max_response_ms': {'type': 'number', 'description': 'Maximum acceptable latency in ms (will be compared if provided)'}}}

{'type': 'object', 'properties': {'total': {'type': 'number'}, 'checks': {}, 'failed': {'type': 'number'}, 'passed': {'type': 'number'}, 'verdict': {'type': 'string'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'URL to validate and parse'}}}

{'type': 'object', 'properties': {'full': {}, 'hash': {}, 'port': {}, 'valid': {'type': 'boolean'}, 'origin': {}, 'search': {}, 'hostname': {}, 'pathname': {}, 'protocol': {}, 'query_params': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['vector'], 'properties': {'bits': {'type': 'number', 'description': 'Quantization bits: 8 (int8, default) or 4 (int4)'}, 'vector': {'type': 'array', 'items': {'type': 'number'}, 'description': 'Float32 vector to quantize'}}}

{'type': 'object', 'properties': {'mse': {'type': 'number'}, 'bits': {}, 'offset': {'type': 'number'}, 'dimension': {'type': 'number'}, 'quantized': {}, 'scale_factor': {'type': 'number'}, 'compression_ratio': {'type': 'string'}, 'storage_bytes_float32': {}, 'storage_bytes_quantized': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['vector_a', 'vector_b'], 'properties': {'metric': {'enum': ['cosine', 'dot_product', 'euclidean', 'manhattan', 'all'], 'type': 'string', 'description': 'Distance metric (default: all)'}, 'vector_a': {'type': 'array', 'items': {'type': 'number'}, 'description': 'First vector as array of floats'}, 'vector_b': {'type': 'array', 'items': {'type': 'number'}, 'description': 'Second vector as array of floats'}}}

{'type': 'object', 'properties': {'norm_a': {}, 'norm_b': {}, 'dimension': {}, 'dot_product': {}, 'interpretation': {}, 'cosine_distance': {}, 'cosine_similarity': {}, 'euclidean_distance': {}, 'manhattan_distance': {}}, 'additionalProperties': True}

{'type': 'object', 'anyOf': [{'required': ['vector']}, {'required': ['matrix']}], 'properties': {'top_k': {'type': 'number', 'description': 'Return indices of top K absolute values (default: 5)'}, 'matrix': {'type': 'array', 'items': {'type': 'array', 'items': {'type': 'number'}}, 'description': 'Matrix of vectors (overrides vector). Returns per-vector + matrix-level stats. Required unless `vector` is given.'}, 'vector': {'type': 'array', 'items': {'type': 'number'}, 'description': 'Single vector to analyze. Required unless `matrix` is given.'}}}

{'type': 'object', 'properties': {'max': {'type': 'number'}, 'min': {'type': 'number'}, 'std': {'type': 'number'}, 'mean': {'type': 'number'}, 'l2_norm': {'type': 'number'}, 'sparsity': {'type': 'number'}, 'dimension': {}, 'per_vector': {}, 'matrix_shape': {'type': 'array'}, 'matrix_stats': {'type': 'object'}, 'top_k_indices': {}}, 'additionalProperties': True}

{'type': 'object', 'properties': {'base_url': {'type': 'string', 'description': 'Optional public base URL. Default: https://www.ia-qa.com/mcp/webhook (the apex ia-qa.com answers 301 and a redirected POST loses its body, so an apex base_url is normalized to www)'}}}

{'type': 'object', 'properties': {'id': {}, 'url': {'type': 'string'}, 'expires_at': {'type': 'string'}, 'request_count': {'type': 'number'}, 'retention_minutes': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'string', 'description': 'Webhook id returned by webhook_endpoint_create'}, 'limit': {'type': 'number', 'description': 'Maximum number of requests to return (1-100, default: 20)'}}}

{'type': 'object', 'properties': {'id': {'type': 'string'}, 'requests': {'type': 'array'}, 'expires_at': {'type': 'string'}, 'request_count': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['url'], 'properties': {'url': {'type': 'string', 'description': 'Full URL to audit (e.g. https://example.com)'}, 'model': {'type': 'string', 'description': 'LLM model for AI analysis (default: "openai/gpt-oss-20b"). Set to "none" to skip AI analysis.'}, 'api_key': {'type': 'string', 'description': 'Your Groq or HuggingFace API key. Required to enable AI analysis.'}}}

{'type': 'object', 'properties': {'fix': {}, 'key': {}, 'url': {}, 'name': {}, 'weak': {}, 'grade': {}, 'score': {}, 'tests': {}, 'value': {}, 'header': {}, 'issues': {}, 'secure': {}, 'weight': {}, 'cookies': {'type': 'array'}, 'details': {}, 'message': {'type': 'string'}, 'missing': {}, 'httpOnly': {}, 'sameSite': {}, 'risk_level': {}, 'weak_count': {'type': 'number'}, 'cookies_found': {'type': 'number'}, 'missing_count': {'type': 'number'}, 'overall_grade': {}, 'origins_tested': {'type': 'number'}, 'total_findings': {'type': 'number'}, 'headers_checked': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'Text to analyze'}, 'top_n': {'type': 'number', 'description': 'Return top N words (default: 20, max: 200)'}, 'min_length': {'type': 'number', 'description': 'Minimum word length to include (default: 3)'}, 'remove_stopwords': {'type': 'boolean', 'description': 'Remove common English stopwords (default: true)'}}}

{'type': 'object', 'properties': {'top_words': {'type': 'array'}, 'total_words': {}, 'unique_words': {'type': 'number'}, 'stopwords_removed': {}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'XML string to convert'}, 'attr_prefix': {'type': 'string', 'description': 'Prefix for attribute keys (default: "@_")'}, 'ignore_attrs': {'type': 'boolean', 'description': 'Ignore XML attributes (default: false)'}, 'parse_values': {'type': 'boolean', 'description': 'Auto-parse numbers and booleans (default: true)'}}}

{'type': 'object', 'properties': {'result': {}, 'key_count': {'type': 'number'}}, 'additionalProperties': True}

{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'string', 'description': 'YAML string to parse'}, 'multi': {'type': 'boolean', 'description': 'If true, parse all documents in a multi-document stream and return an array (default: false)'}}}

{'type': 'object', 'properties': {'json': {}, 'count': {'type': 'number'}, 'documents': {}}, 'additionalProperties': True}