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Marcwarn

doings-evidence-mcp

by Marcwarn

critique_claim

Critically evaluate organization-design or transformation claims using research evidence, with automatic full-text retrieval and context-fit scoring.

Instructions

Critically assesses an organization-design or transformation claim against available research, attempting open-access full-text escalation by default. Includes claim decomposition, level-of-analysis checks, context-fit scoring, study-type classification, passage extraction and optional red-team mode. For user-facing wording use critique_org_text.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
claimYes
contextNo
strictnessNohigh
yearFromNo
maxPapersNo
fullTextModeNoopen_access
maxFullTextPapersNo
maxFullTextCharsPerPaperNo
redTeamModeNo
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses key behaviors: default open-access full-text escalation, claim decomposition, level-of-analysis checks, etc. However, with no annotations, it should ideally specify potential side effects, permissions, or what happens when full-text is unavailable. The listed components add context but lack completeness.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is highly concise: three sentences that succinctly capture purpose, components, and sibling differentiation. No redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 9 parameters and no output schema or annotations, the description is insufficient. It lacks parameter descriptions and return value information, making it incomplete for an agent to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It gives high-level process components but does not explain individual parameters like 'strictness', 'yearFrom', or 'fullTextMode'. This leaves the agent without crucial guidance on parameter usage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool critically assesses an organization-design or transformation claim against research, with specific verb and resource. It also distinguishes from the sibling 'critique_org_text' for user-facing wording, eliminating confusion.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool (assessing claims against research) and explicitly directs to use 'critique_org_text' for user-facing wording. However, it does not mention when not to use it or differentiate from other siblings like 'classify_claims' or 'search_research_evidence'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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