此 MCP 可以做什么
Provides eDiscovery news and calculators for TAR recall, elusion, prevalence, sampling, precision, and review metrics.
功能
工具
15
工具
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.
只读
幂等
输入模式
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['relevant_found', 'relevant_missed'], 'properties': {'relevant_found': {'type': 'integer', 'minimum': 0}, 'relevant_missed': {'type': 'integer', 'minimum': 0}, 'confidence_level': {'type': 'number', 'default': 0.95, 'exclusiveMaximum': 1, 'exclusiveMinimum': 0}}, 'additionalProperties': False}
输出模式
{'type': 'object', '$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.
只读
幂等
输入模式
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['relevant_found_in_sample', 'sample_size'], 'properties': {'sample_size': {'type': 'integer', 'exclusiveMinimum': 0}, 'confidence_level': {'type': 'number', 'default': 0.95, 'exclusiveMaximum': 1, 'exclusiveMinimum': 0}, 'relevant_found_in_sample': {'type': 'integer', 'minimum': 0}}, 'additionalProperties': False}
输出模式
{'type': 'object', '$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.
只读
幂等
输入模式
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['positive_hits', 'sample_size'], 'properties': {'sample_size': {'type': 'integer', 'exclusiveMinimum': 0}, 'positive_hits': {'type': 'integer', 'minimum': 0}, 'population_size': {'type': 'integer', 'exclusiveMinimum': 0}, 'confidence_level': {'type': 'number', 'default': 0.95, 'exclusiveMaximum': 1, 'exclusiveMinimum': 0}}, 'additionalProperties': False}
输出模式
{'type': 'object', '$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.
只读
幂等
输入模式
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['true_positives', 'false_positives', 'false_negatives', 'true_negatives'], 'properties': {'true_negatives': {'type': 'integer', 'minimum': 0}, 'true_positives': {'type': 'integer', 'minimum': 0}, 'false_negatives': {'type': 'integer', 'minimum': 0}, 'false_positives': {'type': 'integer', 'minimum': 0}}, 'additionalProperties': False}
输出模式
{'type': 'object', '$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.
只读
幂等
输入模式
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['population_size', 'margin_of_error'], 'properties': {'margin_of_error': {'type': 'number', 'exclusiveMaximum': 1, 'exclusiveMinimum': 0}, 'population_size': {'type': 'integer', 'exclusiveMinimum': 0}, 'confidence_level': {'type': 'number', 'default': 0.95, 'exclusiveMaximum': 1, 'exclusiveMinimum': 0}, 'estimated_prevalence': {'type': 'number', 'default': 0.5, 'maximum': 1, 'minimum': 0}}, 'additionalProperties': False}
输出模式
{'type': 'object', '$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.
只读
幂等
输入模式
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['responsive_found', 'excluded_population_size', 'elusion_responsive_hits', 'elusion_sample_size'], 'properties': {'confidence_level': {'type': 'number', 'default': 0.95, 'exclusiveMaximum': 1, 'exclusiveMinimum': 0}, 'responsive_found': {'type': 'integer', 'minimum': 0}, 'elusion_sample_size': {'type': 'integer', 'exclusiveMinimum': 0}, 'elusion_responsive_hits': {'type': 'integer', 'minimum': 0}, 'excluded_population_size': {'type': 'integer', 'minimum': 0}}, 'additionalProperties': False}
输出模式
{'type': 'object', '$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.
只读
幂等
输入模式
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['scored_document_count', 'cutoffs'], 'properties': {'cutoffs': {'type': 'array', 'items': {'type': 'object', 'required': ['cutoff', 'document_count'], 'properties': {'label': {'type': 'string', 'minLength': 1}, 'cutoff': {'type': 'number'}, 'document_count': {'type': 'integer', 'minimum': 0}, 'responsive_count': {'type': 'integer', 'minimum': 0}}, 'additionalProperties': False}, 'minItems': 1}, 'scored_document_count': {'type': 'integer', 'exclusiveMinimum': 0}}, 'additionalProperties': False}
输出模式
{'type': 'object', '$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.
只读
幂等
输入模式
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'properties': {}}
输出模式
{'type': 'object', '$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.
只读
可访问外部资源
幂等
输入模式
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'properties': {'week_limit': {'type': 'integer', 'default': 3, 'maximum': 10, 'minimum': 1}, 'current_limit': {'type': 'integer', 'default': 7, 'maximum': 20, 'minimum': 1}}, 'additionalProperties': False}
输出模式
{'type': 'object', '$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': {'$ref': '#/properties/top_stories/items/properties/published_at'}, 'why_it_matters': {'type': 'string'}, 'score_breakdown': {'type': 'object', 'additionalProperties': {'type': 'number'}}}, 'additionalProperties': False}}, 'source_url': {'type': 'string'}, 'generated_at': {'type': 'string'}}, 'additionalProperties': False}, 'generated_at': {'type': 'string'}, 'story_bullets': {'type': 'array', 'items': {'type': 'object', 'required': ['id', 'title', 'summary', 'source_url', 'published_at', 'tags', 'why_it_matters'], 'properties': {'id': {'type': 'string'}, 'tags': {'type': 'array', 'items': {'type': 'string'}}, 'title': {'type': 'string'}, 'summary': {'type': 'string'}, 'source_url': {'type': 'string'}, 'published_at': {'type': 'string'}, 'why_it_matters': {'type': 'string'}}, 'additionalProperties': False}}, 'formatted_brief': {'type': 'string'}}, 'additionalProperties': False}
get_prompt_template
Get MCP Prompt Template
Return the rendered text of one of this server's guided prompts (mcp-demo-tour, tar-matter-kickoff, weekly-digest). Use when the client can call tools but cannot open MCP prompts directly, or when you want to inspect a prompt's wording before using it.
只读
幂等
输入模式
{'type': 'object', '$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}$'}, 'prompt_name': {'enum': ['mcp-demo-tour', 'tar-matter-kickoff', 'weekly-digest'], 'type': 'string'}, 'matter_description': {'type': 'string', 'minLength': 1}}, 'additionalProperties': False}
输出模式
{'type': 'object', '$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.
只读
幂等
输入模式
{'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}
输出模式
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['uri', 'mimeType', 'text', 'payload'], 'properties': {'uri': {'type': 'string'}, 'text': {'type': 'string'}, 'payload': {'type': 'object', 'additionalProperties': {}}, 'mimeType': {'type': 'string'}}, 'additionalProperties': False}
list_capabilities
List eDiscovery Decoder MCP Capabilities
List the full eDiscovery Decoder MCP surface — every tool, prompt, and resource, plus the suggested demo flow and safety boundaries — with an example prompt for each. Call this first when you are unsure which tool fits the user's question, or when tool-search shows only a partial list.
只读
幂等
输入模式
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'properties': {}}
输出模式
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['server', 'version', 'purpose', 'endpoint', 'tools', 'prompts', 'resources', 'demo_flow', 'safety_boundaries', 'claude_note'], 'properties': {'tools': {'type': 'array', 'items': {'type': 'object', 'required': ['name', 'purpose', 'example_prompt'], 'properties': {'name': {'type': 'string'}, 'purpose': {'type': 'string'}, 'example_prompt': {'type': 'string'}}, 'additionalProperties': False}}, 'server': {'type': 'string'}, 'prompts': {'type': 'array', 'items': {'type': 'object', 'required': ['name', 'purpose'], 'properties': {'name': {'type': 'string'}, 'purpose': {'type': 'string'}}, 'additionalProperties': False}}, 'purpose': {'type': 'string'}, 'version': {'type': 'string'}, 'endpoint': {'type': 'string'}, 'demo_flow': {'type': 'array', 'items': {'type': 'string'}}, 'resources': {'type': 'array', 'items': {'type': 'object', 'required': ['uri', 'purpose'], 'properties': {'uri': {'type': 'string'}, 'purpose': {'type': 'string'}}, 'additionalProperties': False}}, 'claude_note': {'type': 'string'}, 'safety_boundaries': {'type': 'array', 'items': {'type': 'string'}}}, 'additionalProperties': False}
ping
Ping
Health check: confirm the eDiscovery Decoder News/Calc MCP server is reachable before a demo or when troubleshooting a connection. Returns server name and version. No inputs.
只读
幂等
输入模式
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'properties': {}}
输出模式
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['ok', 'server', 'version'], 'properties': {'ok': {'type': 'boolean'}, 'server': {'type': 'string'}, 'version': {'type': 'string'}}, 'additionalProperties': False}
search_news
Search eDiscovery News
Find recent eDiscovery / legal-AI / TAR news by topic, tag, or date range. Use when the user asks what's new or recent in eDiscovery, wants stories on a subject, or asks about a time window. For a ready-made top-stories roundup instead, use get_news_brief.
只读
可访问外部资源
幂等
输入模式
{'type': 'object', '$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}
输出模式
{'type': 'object', '$schema': 'http://json-schema.org/draft-07/schema#', 'required': ['items'], 'properties': {'items': {'type': 'array', 'items': {'type': 'object', 'required': ['id', 'title', 'summary', 'source_url', 'published_at', 'tags'], 'properties': {'id': {'type': 'string'}, 'tags': {'type': 'array', 'items': {'type': 'string'}}, 'title': {'type': 'string'}, 'summary': {'type': 'string'}, 'source_url': {'type': 'string'}, 'published_at': {'type': 'string'}}, 'additionalProperties': False}}}, 'additionalProperties': False}
validate_sample_design
Validate Sample Design
QC a TAR validation sampling plan: check whether it has the documented elements needed for a defensibility discussion (population, sample size, confidence level, sampling frame/method, randomization, etc.) and flag what is missing or inconsistent. Use to sanity-check a sampling protocol before relying on it. Reviews metadata only — not a legal sufficiency opinion.
只读
幂等
输入模式
{'type': 'object', '$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}
输出模式
{'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}
历史
近期工具变更
已添加
validate_sample_design
2026年9月17日 12:34
已添加
compare_tar_cutoffs
2026年9月17日 12:34
已添加
calculate_control_set_recall
2026年9月17日 12:34
已添加
calculate_prevalence_richness
2026年9月17日 12:34
已添加
calculate_tar_recall_estimate
2026年9月17日 12:34
已添加
calculate_sample_size
2026年9月17日 12:34
已添加
calculate_elusion
2026年9月17日 12:34
已添加
calculate_review_metrics
2026年9月17日 12:34
已添加
get_news_brief
2026年9月17日 12:34
已添加
search_news
2026年9月17日 12:34
已添加
get_prompt_template
2026年9月17日 12:34
已添加
get_resource_content
2026年9月17日 12:34
已添加
get_demo_guide
2026年9月17日 12:34
已添加
list_capabilities
2026年9月17日 12:34
已添加
ping
2026年9月17日 12:34
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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…