MCP-Server
eDiscovery Decoder News/Calc
com.ediscoverydecoder/mcp
Was dieses MCP kann
Provides eDiscovery news and calculators for TAR recall, elusion, prevalence, sampling, precision, and review metrics.
Funktionen
Tools
15
Tools
calculate_control_set_recall
Calculate Control Set Recall
Calculate recall against a known control set: the share of documents already confirmed relevant that the workflow found, with a Wilson confidence interval. Use when you have relevant-found and relevant-missed counts from a fixed reference set. For recall from a confusion matrix use calculate_review_metrics; from a discard-set sample use calculate_tar_recall_estimate. Aggregate counts only; not legal advice.
Nur Lesen
Idempotent
Eingabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['relevant_found', 'relevant_missed'], 'properties': {'relevant_found': {'type': 'integer', 'minimum': 0}, 'relevant_missed': {'type': 'integer', 'minimum': 0}, 'confidence_level': {'type': 'number', 'default': 0.95, 'exclusiveMaximum': 1, 'exclusiveMinimum': 0}}, 'additionalProperties': False}
Ausgabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['relevantFound', 'relevantMissed', 'totalRelevant', 'recall', 'confidenceInterval', 'confidenceLevel', 'formula'], 'properties': {'recall': {'type': ['number', 'null']}, 'formula': {'type': 'string'}, 'relevantFound': {'type': 'integer', 'minimum': 0}, 'totalRelevant': {'type': 'integer', 'minimum': 0}, 'relevantMissed': {'type': 'integer', 'minimum': 0}, 'confidenceLevel': {'type': 'number'}, 'confidenceInterval': {'type': 'object', 'required': ['lower', 'upper', 'method'], 'properties': {'lower': {'type': ['number', 'null']}, 'upper': {'type': ['number', 'null']}, 'method': {'type': 'string', 'const': 'wilson'}}, 'additionalProperties': False}}, 'additionalProperties': False}
calculate_elusion
Calculate Elusion
Estimate how much responsive/relevant material may remain in a set you chose NOT to review (the discard, null, or 'elusion' set). Use when a random sample of that excluded set has been coded — e.g. 'we sampled 400 culled docs and found 2 relevant.' Returns the elusion rate and a Wilson confidence interval. For an overall recall % from the same sample, use calculate_tar_recall_estimate. Aggregate counts only; not legal advice.
Nur Lesen
Idempotent
Eingabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['relevant_found_in_sample', 'sample_size'], 'properties': {'sample_size': {'type': 'integer', 'exclusiveMinimum': 0}, 'confidence_level': {'type': 'number', 'default': 0.95, 'exclusiveMaximum': 1, 'exclusiveMinimum': 0}, 'relevant_found_in_sample': {'type': 'integer', 'minimum': 0}}, 'additionalProperties': False}
Ausgabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['elusion_rate', 'confidence_interval', 'formula', 'assumptions'], 'properties': {'formula': {'type': 'string'}, 'assumptions': {'type': 'object', 'required': ['relevant_found_in_sample', 'sample_size', 'confidence_level', 'z_score'], 'properties': {'z_score': {'type': 'number'}, 'sample_size': {'type': 'number'}, 'confidence_level': {'type': 'number'}, 'relevant_found_in_sample': {'type': 'number'}}, 'additionalProperties': False}, 'elusion_rate': {'type': 'number'}, 'confidence_interval': {'type': 'object', 'required': ['lower', 'upper', 'method'], 'properties': {'lower': {'type': 'number'}, 'upper': {'type': 'number'}, 'method': {'type': 'string', 'const': 'wilson'}}, 'additionalProperties': False}}, 'additionalProperties': False}
calculate_prevalence_richness
Calculate Prevalence Or Richness
Estimate how rich or prevalent a population is — the share that is responsive/relevant/positive — from positive hits in a random sample, with a Wilson confidence interval. Use for 'what % of this set is relevant?' or to size review scope and cost expectations. Aggregate counts only; not legal advice.
Nur Lesen
Idempotent
Eingabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['positive_hits', 'sample_size'], 'properties': {'sample_size': {'type': 'integer', 'exclusiveMinimum': 0}, 'positive_hits': {'type': 'integer', 'minimum': 0}, 'population_size': {'type': 'integer', 'exclusiveMinimum': 0}, 'confidence_level': {'type': 'number', 'default': 0.95, 'exclusiveMaximum': 1, 'exclusiveMinimum': 0}}, 'additionalProperties': False}
Ausgabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['sampleSize', 'positiveHits', 'pointEstimate', 'confidenceInterval', 'confidenceLevel', 'estimatedPositiveCount', 'estimatedPositiveLower', 'estimatedPositiveUpper', 'formula'], 'properties': {'formula': {'type': 'string'}, 'sampleSize': {'type': 'integer', 'minimum': 0}, 'positiveHits': {'type': 'integer', 'minimum': 0}, 'pointEstimate': {'type': 'number'}, 'confidenceLevel': {'type': 'number'}, 'confidenceInterval': {'type': 'object', 'required': ['lower', 'upper', 'method'], 'properties': {'lower': {'type': 'number'}, 'upper': {'type': 'number'}, 'method': {'type': 'string', 'const': 'wilson'}}, 'additionalProperties': False}, 'estimatedPositiveCount': {'type': ['number', 'null']}, 'estimatedPositiveLower': {'type': ['number', 'null']}, 'estimatedPositiveUpper': {'type': ['number', 'null']}}, 'additionalProperties': False}
calculate_review_metrics
Calculate Review Metrics
Score a coded sample when you have a full confusion matrix (true/false positives and negatives) — e.g. comparing a TAR model's calls against a reviewer's. Returns recall, precision, F1, accuracy, and in-sample elusion. Use calculate_control_set_recall if you only have relevant-found vs relevant-missed; calculate_elusion for a discard/null-set sample. Aggregate counts only; not legal advice.
Nur Lesen
Idempotent
Eingabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['true_positives', 'false_positives', 'false_negatives', 'true_negatives'], 'properties': {'true_negatives': {'type': 'integer', 'minimum': 0}, 'true_positives': {'type': 'integer', 'minimum': 0}, 'false_negatives': {'type': 'integer', 'minimum': 0}, 'false_positives': {'type': 'integer', 'minimum': 0}}, 'additionalProperties': False}
Ausgabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['recall', 'precision', 'f1', 'accuracy', 'elusion_in_sample'], 'properties': {'f1': {'$ref': '#/properties/recall'}, 'recall': {'type': 'object', 'required': ['value', 'formula'], 'properties': {'note': {'type': 'string'}, 'value': {'type': ['number', 'null']}, 'formula': {'type': 'string'}}, 'additionalProperties': False}, 'accuracy': {'$ref': '#/properties/recall'}, 'precision': {'$ref': '#/properties/recall'}, 'elusion_in_sample': {'$ref': '#/properties/recall'}}, 'additionalProperties': False}
calculate_sample_size
Calculate Sample Size
Work out how many documents to randomly sample to estimate a proportion (e.g. richness or elusion) at a target confidence level and margin of error, with finite-population correction. Use when planning a sample before review — 'how big a sample do we need?' Aggregate inputs only; not legal advice.
Nur Lesen
Idempotent
Eingabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['population_size', 'margin_of_error'], 'properties': {'margin_of_error': {'type': 'number', 'exclusiveMaximum': 1, 'exclusiveMinimum': 0}, 'population_size': {'type': 'integer', 'exclusiveMinimum': 0}, 'confidence_level': {'type': 'number', 'default': 0.95, 'exclusiveMaximum': 1, 'exclusiveMinimum': 0}, 'estimated_prevalence': {'type': 'number', 'default': 0.5, 'maximum': 1, 'minimum': 0}}, 'additionalProperties': False}
Ausgabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['recommended_sample_size', 'raw_sample_size', 'assumptions', 'formula'], 'properties': {'formula': {'type': 'string'}, 'assumptions': {'type': 'object', 'required': ['population_size', 'confidence_level', 'margin_of_error', 'estimated_prevalence', 'z_score'], 'properties': {'z_score': {'type': 'number'}, 'margin_of_error': {'type': 'number'}, 'population_size': {'type': 'number'}, 'confidence_level': {'type': 'number'}, 'estimated_prevalence': {'type': 'number'}}, 'additionalProperties': False}, 'raw_sample_size': {'type': 'number', 'minimum': 0}, 'recommended_sample_size': {'type': 'integer', 'minimum': 0}}, 'additionalProperties': False}
calculate_tar_recall_estimate
Calculate TAR Recall Estimate
Estimate overall TAR recall and how many responsive docs were missed, by combining the responsive count already found with an elusion sample of the excluded set. Use when the user wants a recall % for the whole workflow, not just the elusion rate. For only the elusion rate and its interval, use calculate_elusion. Aggregate counts only; not legal advice.
Nur Lesen
Idempotent
Eingabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['responsive_found', 'excluded_population_size', 'elusion_responsive_hits', 'elusion_sample_size'], 'properties': {'confidence_level': {'type': 'number', 'default': 0.95, 'exclusiveMaximum': 1, 'exclusiveMinimum': 0}, 'responsive_found': {'type': 'integer', 'minimum': 0}, 'elusion_sample_size': {'type': 'integer', 'exclusiveMinimum': 0}, 'elusion_responsive_hits': {'type': 'integer', 'minimum': 0}, 'excluded_population_size': {'type': 'integer', 'minimum': 0}}, 'additionalProperties': False}
Ausgabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['responsiveFound', 'excludedPopulationSize', 'elusion', 'estimatedRecall', 'formula', 'assumptions'], 'properties': {'elusion': {'type': 'object', 'required': ['sampleSize', 'responsiveHits', 'pointEstimate', 'confidenceInterval', 'estimatedMissed', 'estimatedMissedLower', 'estimatedMissedUpper', 'confidenceLevel'], 'properties': {'sampleSize': {'type': 'integer', 'minimum': 0}, 'pointEstimate': {'type': ['number', 'null']}, 'responsiveHits': {'type': 'integer', 'minimum': 0}, 'confidenceLevel': {'type': 'number'}, 'estimatedMissed': {'type': ['number', 'null']}, 'confidenceInterval': {'type': 'object', 'required': ['lower', 'upper', 'method'], 'properties': {'lower': {'type': ['number', 'null']}, 'upper': {'type': ['number', 'null']}, 'method': {'type': 'string', 'const': 'wilson'}}, 'additionalProperties': False}, 'estimatedMissedLower': {'type': ['number', 'null']}, 'estimatedMissedUpper': {'type': ['number', 'null']}}, 'additionalProperties': False}, 'formula': {'type': 'string'}, 'assumptions': {'type': 'array', 'items': {'type': 'string'}}, 'estimatedRecall': {'anyOf': [{'type': 'object', 'required': ['estimate', 'lower', 'upper'], 'properties': {'lower': {'type': 'number'}, 'upper': {'type': 'number'}, 'estimate': {'type': 'number'}}, 'additionalProperties': False}, {'type': 'null'}]}, 'responsiveFound': {'type': 'integer', 'minimum': 0}, 'excludedPopulationSize': {'type': 'integer', 'minimum': 0}}, 'additionalProperties': False}
compare_tar_cutoffs
Compare TAR Cutoffs
Compare candidate TAR score or rank cutoffs side by side: for each cutoff, how many docs sit above it, its share of the scored set, and (if responsive counts are given) an estimated precision. Use when deciding where to draw the review/cull line. Aggregate counts only; not legal advice.
Nur Lesen
Idempotent
Eingabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['scored_document_count', 'cutoffs'], 'properties': {'cutoffs': {'type': 'array', 'items': {'type': 'object', 'required': ['cutoff', 'document_count'], 'properties': {'label': {'type': 'string', 'minLength': 1}, 'cutoff': {'type': 'number'}, 'document_count': {'type': 'integer', 'minimum': 0}, 'responsive_count': {'type': 'integer', 'minimum': 0}}, 'additionalProperties': False}, 'minItems': 1}, 'scored_document_count': {'type': 'integer', 'exclusiveMinimum': 0}}, 'additionalProperties': False}
Ausgabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['scoredDocumentCount', 'cutoffs', 'questions'], 'properties': {'cutoffs': {'type': 'array', 'items': {'type': 'object', 'required': ['label', 'cutoff', 'documentCount', 'shareOfScored', 'responsiveCount', 'precisionEstimate'], 'properties': {'label': {'type': 'string'}, 'cutoff': {'type': 'number'}, 'documentCount': {'type': 'integer', 'minimum': 0}, 'shareOfScored': {'type': 'number'}, 'responsiveCount': {'anyOf': [{'type': 'integer', 'minimum': 0}, {'type': 'null'}]}, 'precisionEstimate': {'type': ['number', 'null']}}, 'additionalProperties': False}}, 'questions': {'type': 'array', 'items': {'type': 'string'}}, 'scoredDocumentCount': {'type': 'integer', 'exclusiveMinimum': 0}}, 'additionalProperties': False}
get_demo_guide
Get eDiscovery Decoder MCP Demo Guide
Return a short, human-readable walkthrough for testing this server: the endpoint, the tool/prompt/resource names, and ready-to-paste sample prompts. Use to give someone a guided demo. For the full machine-readable capability catalog, use list_capabilities instead.
Nur Lesen
Idempotent
Eingabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'properties': {}}
Ausgabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['title', 'endpoint', 'purpose', 'tools', 'prompts', 'resources', 'suggested_test_prompts', 'safety_boundaries'], 'properties': {'title': {'type': 'string'}, 'tools': {'type': 'array', 'items': {'type': 'string'}}, 'prompts': {'type': 'array', 'items': {'type': 'string'}}, 'purpose': {'type': 'string'}, 'endpoint': {'type': 'string'}, 'resources': {'type': 'array', 'items': {'type': 'string'}}, 'safety_boundaries': {'type': 'array', 'items': {'type': 'string'}}, 'suggested_test_prompts': {'type': 'array', 'items': {'type': 'string'}}}, 'additionalProperties': False}
get_news_brief
Get eDiscovery News Brief
Get the current eDiscovery Decoder news brief: top stories plus a Week in Review breakdown, returned both as structured data and as display-ready Markdown (formatted_brief) with a 'why it matters' line per story. Use when the user wants a roundup or summary of current eDiscovery AI news rather than a keyword search.
Nur Lesen
Externer Zugriff
Idempotent
Eingabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'properties': {'week_limit': {'type': 'integer', 'default': 3, 'maximum': 10, 'minimum': 1}, 'current_limit': {'type': 'integer', 'default': 7, 'maximum': 20, 'minimum': 1}}, 'additionalProperties': False}
Ausgabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['generated_at', 'source_url', 'formatted_brief', 'story_bullets', 'top_stories', 'week_so_far'], 'properties': {'source_url': {'type': 'string'}, 'top_stories': {'type': 'array', 'items': {'type': 'object', 'required': ['id', 'title', 'summary', 'source_url', 'published_at', 'tags'], 'properties': {'id': {'type': 'string'}, 'tags': {'type': 'array', 'items': {'type': 'string'}}, 'title': {'type': 'string'}, 'summary': {'type': 'string'}, 'source_url': {'type': 'string'}, 'published_at': {'type': 'string'}}, 'additionalProperties': False}}, 'week_so_far': {'type': 'object', 'required': ['generated_at', 'source_url', 'items', 'breakdowns'], 'properties': {'items': {'type': 'array', 'items': {'$ref': '#/properties/top_stories/items'}}, 'breakdowns': {'type': 'array', 'items': {'type': 'object', 'required': ['id', 'title', 'summary', 'source_url', 'published_at', 'tags'], 'properties': {'id': {'$ref': '#/properties/top_stories/items/properties/id'}, 'tags': {'$ref': '#/properties/top_stories/items/properties/tags'}, 'score': {'type': 'number'}, 'title': {'$ref': '#/properties/top_stories/items/properties/title'}, 'reasons': {'type': 'array', 'items': {'type': 'string'}}, 'summary': {'$ref': '#/properties/top_stories/items/properties/summary'}, 'source_url': {'$ref': '#/properties/top_stories/items/properties/source_url'}, 'published_at': {'$ref': '#/properties/top_stories/items/properties/published_at'}, 'why_it_matters': {'type': 'string'}, 'score_breakdown': {'type': 'object', 'additionalProperties': {'type': 'number'}}}, 'additionalProperties': False}}, 'source_url': {'type': 'string'}, 'generated_at': {'type': 'string'}}, 'additionalProperties': False}, 'generated_at': {'type': 'string'}, 'story_bullets': {'type': 'array', 'items': {'type': 'object', 'required': ['id', 'title', 'summary', 'source_url', 'published_at', 'tags', 'why_it_matters'], 'properties': {'id': {'type': 'string'}, 'tags': {'type': 'array', 'items': {'type': 'string'}}, 'title': {'type': 'string'}, 'summary': {'type': 'string'}, 'source_url': {'type': 'string'}, 'published_at': {'type': 'string'}, 'why_it_matters': {'type': 'string'}}, 'additionalProperties': False}}, 'formatted_brief': {'type': 'string'}}, 'additionalProperties': False}
get_prompt_template
Get MCP Prompt Template
Return the rendered text of one of this server's guided prompts (mcp-demo-tour, tar-matter-kickoff, weekly-digest). Use when the client can call tools but cannot open MCP prompts directly, or when you want to inspect a prompt's wording before using it.
Nur Lesen
Idempotent
Eingabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['prompt_name'], 'properties': {'audience': {'type': 'string', 'minLength': 1}, 'week_start': {'type': 'string', 'pattern': '^\\d{4}-\\d{2}-\\d{2}$'}, 'prompt_name': {'enum': ['mcp-demo-tour', 'tar-matter-kickoff', 'weekly-digest'], 'type': 'string'}, 'matter_description': {'type': 'string', 'minLength': 1}}, 'additionalProperties': False}
Ausgabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['name', 'arguments', 'template_text', 'messages'], 'properties': {'name': {'type': 'string'}, 'messages': {'type': 'array', 'items': {'type': 'object', 'required': ['role', 'content'], 'properties': {'role': {'enum': ['user', 'assistant'], 'type': 'string'}, 'content': {'type': 'object', 'required': ['type', 'text'], 'properties': {'text': {'type': 'string'}, 'type': {'type': 'string', 'const': 'text'}}, 'additionalProperties': False}}, 'additionalProperties': False}}, 'arguments': {'type': 'object', 'additionalProperties': {'type': 'string'}}, 'description': {'type': 'string'}, 'template_text': {'type': 'string'}}, 'additionalProperties': False}
get_resource_content
Get MCP Resource Content
Fetch the JSON behind a supported edd:// resource — the demo guide, TAR learning path, glossary, or news (latest / brief / by-date). Use when you want resource content but the client cannot read MCP resources directly, e.g. to pull glossary definitions or the news brief as a normal tool result.
Nur Lesen
Idempotent
Eingabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['uri'], 'properties': {'uri': {'type': 'string', 'pattern': '^edd:\\/\\/(?:mcp\\/demo-guide|resources\\/tar-learning-path|glossary\\/core|news\\/latest|news\\/brief|news\\/\\d{4}-\\d{2}-\\d{2})$'}}, 'additionalProperties': False}
Ausgabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['uri', 'mimeType', 'text', 'payload'], 'properties': {'uri': {'type': 'string'}, 'text': {'type': 'string'}, 'payload': {'type': 'object', 'additionalProperties': {}}, 'mimeType': {'type': 'string'}}, 'additionalProperties': False}
list_capabilities
List eDiscovery Decoder MCP Capabilities
List the full eDiscovery Decoder MCP surface — every tool, prompt, and resource, plus the suggested demo flow and safety boundaries — with an example prompt for each. Call this first when you are unsure which tool fits the user's question, or when tool-search shows only a partial list.
Nur Lesen
Idempotent
Eingabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'properties': {}}
Ausgabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['server', 'version', 'purpose', 'endpoint', 'tools', 'prompts', 'resources', 'demo_flow', 'safety_boundaries', 'claude_note'], 'properties': {'tools': {'type': 'array', 'items': {'type': 'object', 'required': ['name', 'purpose', 'example_prompt'], 'properties': {'name': {'type': 'string'}, 'purpose': {'type': 'string'}, 'example_prompt': {'type': 'string'}}, 'additionalProperties': False}}, 'server': {'type': 'string'}, 'prompts': {'type': 'array', 'items': {'type': 'object', 'required': ['name', 'purpose'], 'properties': {'name': {'type': 'string'}, 'purpose': {'type': 'string'}}, 'additionalProperties': False}}, 'purpose': {'type': 'string'}, 'version': {'type': 'string'}, 'endpoint': {'type': 'string'}, 'demo_flow': {'type': 'array', 'items': {'type': 'string'}}, 'resources': {'type': 'array', 'items': {'type': 'object', 'required': ['uri', 'purpose'], 'properties': {'uri': {'type': 'string'}, 'purpose': {'type': 'string'}}, 'additionalProperties': False}}, 'claude_note': {'type': 'string'}, 'safety_boundaries': {'type': 'array', 'items': {'type': 'string'}}}, 'additionalProperties': False}
ping
Ping
Health check: confirm the eDiscovery Decoder News/Calc MCP server is reachable before a demo or when troubleshooting a connection. Returns server name and version. No inputs.
Nur Lesen
Idempotent
Eingabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'properties': {}}
Ausgabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['ok', 'server', 'version'], 'properties': {'ok': {'type': 'boolean'}, 'server': {'type': 'string'}, 'version': {'type': 'string'}}, 'additionalProperties': False}
search_news
Search eDiscovery News
Find recent eDiscovery / legal-AI / TAR news by topic, tag, or date range. Use when the user asks what's new or recent in eDiscovery, wants stories on a subject, or asks about a time window. For a ready-made top-stories roundup instead, use get_news_brief.
Nur Lesen
Externer Zugriff
Idempotent
Eingabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'properties': {'tags': {'type': 'array', 'items': {'type': 'string', 'minLength': 1}}, 'limit': {'type': 'integer', 'default': 10, 'maximum': 50, 'minimum': 1}, 'query': {'type': 'string', 'minLength': 1}, 'date_to': {'$ref': '#/properties/date_from'}, 'date_from': {'type': 'string', 'pattern': '^\\d{4}-\\d{2}-\\d{2}$'}}, 'additionalProperties': False}
Ausgabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['items'], 'properties': {'items': {'type': 'array', 'items': {'type': 'object', 'required': ['id', 'title', 'summary', 'source_url', 'published_at', 'tags'], 'properties': {'id': {'type': 'string'}, 'tags': {'type': 'array', 'items': {'type': 'string'}}, 'title': {'type': 'string'}, 'summary': {'type': 'string'}, 'source_url': {'type': 'string'}, 'published_at': {'type': 'string'}}, 'additionalProperties': False}}}, 'additionalProperties': False}
validate_sample_design
Validate Sample Design
QC a TAR validation sampling plan: check whether it has the documented elements needed for a defensibility discussion (population, sample size, confidence level, sampling frame/method, randomization, etc.) and flag what is missing or inconsistent. Use to sanity-check a sampling protocol before relying on it. Reviews metadata only — not a legal sufficiency opinion.
Nur Lesen
Idempotent
Eingabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['population_size', 'sample_size'], 'properties': {'random_seed': {'type': 'string', 'minLength': 1}, 'sample_size': {'type': 'integer'}, 'generated_at': {'type': 'string', 'minLength': 1}, 'sampling_frame': {'type': 'string', 'minLength': 1}, 'margin_of_error': {'type': 'number', 'exclusiveMaximum': 1, 'exclusiveMinimum': 0}, 'population_size': {'type': 'integer'}, 'sampling_method': {'type': 'string', 'minLength': 1}, 'confidence_level': {'type': 'number', 'default': 0.95, 'exclusiveMaximum': 1, 'exclusiveMinimum': 0}, 'excluded_population_size': {'type': 'integer'}}, 'additionalProperties': False}
Ausgabeschema
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['status', 'issues', 'summary'], 'properties': {'issues': {'type': 'array', 'items': {'type': 'object', 'required': ['id', 'title', 'severity', 'detail'], 'properties': {'id': {'type': 'string'}, 'title': {'type': 'string'}, 'detail': {'type': 'string'}, 'severity': {'enum': ['info', 'warning', 'critical'], 'type': 'string'}}, 'additionalProperties': False}}, 'status': {'enum': ['ready', 'needs_attention', 'blocked'], 'type': 'string'}, 'summary': {'type': 'object', 'required': ['populationSize', 'sampleSize', 'samplingRate', 'confidenceLevel', 'marginOfError'], 'properties': {'sampleSize': {'type': 'integer'}, 'samplingRate': {'type': ['number', 'null']}, 'marginOfError': {'type': ['number', 'null']}, 'populationSize': {'type': 'integer'}, 'confidenceLevel': {'type': 'number'}}, 'additionalProperties': False}}, 'additionalProperties': False}
Verlauf
Letzte Tool-Änderungen
Hinzugefügt
validate_sample_design
17. September 2026 12:34
Hinzugefügt
compare_tar_cutoffs
17. September 2026 12:34
Hinzugefügt
calculate_control_set_recall
17. September 2026 12:34
Hinzugefügt
calculate_prevalence_richness
17. September 2026 12:34
Hinzugefügt
calculate_tar_recall_estimate
17. September 2026 12:34
Hinzugefügt
calculate_sample_size
17. September 2026 12:34
Hinzugefügt
calculate_elusion
17. September 2026 12:34
Hinzugefügt
calculate_review_metrics
17. September 2026 12:34
Hinzugefügt
get_news_brief
17. September 2026 12:34
Hinzugefügt
search_news
17. September 2026 12:34
Hinzugefügt
get_prompt_template
17. September 2026 12:34
Hinzugefügt
get_resource_content
17. September 2026 12:34
Hinzugefügt
get_demo_guide
17. September 2026 12:34
Hinzugefügt
list_capabilities
17. September 2026 12:34
Hinzugefügt
ping
17. September 2026 12:34
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Edgar
io.github.pipeworx-io/edgar
Accesses SEC EDGAR filings, XBRL financial facts, filing text, ownership, insider transactions, fund holdings, and company classi…
Cms Open Payments
io.github.pipeworx-io/cms-open-payments
Searches and analyzes CMS Open Payments data on payments from pharmaceutical and device companies to physicians, hospitals, and o…
Sec Xbrl
io.github.pipeworx-io/sec-xbrl
Retrieves and analyzes SEC EDGAR XBRL company facts, financial statements, capital-market filings, dilution, liquidity, and R&D m…
Epa Echo
io.github.pipeworx-io/epa-echo
Searches EPA-regulated facilities and retrieves environmental compliance histories, violations, enforcement actions, and penaltie…