evaluate_claim

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

Annotations already indicate readOnlyHint=true and destructiveHint=false, so the tool is safe to invoke. The description adds critical behavioral context: 'A screen is free and needs no token. A full attested dossier (deep) is the signed, independently re-checkable audit and needs access.' It also explains output includes 'sources cited by hard id (PMID, DOI, NCT, NIH grant, SEC filing)'. This goes beyond annotations and provides actionable guidance.

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

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

The description is front-loaded with the core purpose in the first sentence. It then provides context, use cases, and parameter details. While verbose, every sentence adds value—no filler. The structure is logical, moving from general purpose to specific parameters and modes.

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

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

Given the complexity (5 parameters, 1 required, 0% schema coverage) and the presence of an output schema, the description provides sufficient context: it explains all parameters, usage scenarios, and output characteristics (sources with IDs). It does not redundantly describe return values since an output schema exists. Minor gap: does not elaborate on the 'overall reading' grade format, but this is covered by the output schema.

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

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

Schema description coverage is 0%, but the description explains each parameter inline: claim ('one or two sentences'), depth ('screen' for fast free, 'deep' for full dossier), mode ('research' or 'diligence'), context (optional background), documents (optional source text). This adds meaningful semantics beyond the schema's titles and defaults, though it could be more structured.

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

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

The description clearly states the tool evaluates how rigorously a scientific, biomedical, clinical, or AI/ML claim was derived and how well evidence supports it. It provides a specific verb ('evaluate') and resource ('claim'), with a detailed scope that distinguishes it from general search tools. Sibling tools (check_evaluation, verify_attestation) are different functions, but the description's specificity makes its purpose unambiguous.

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

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

The description explicitly says 'Use this whenever someone wants to assess, screen, sanity-check, or do due diligence on a research claim...' and lists concrete contexts (study, paper, grant, pitch). It distinguishes between 'screen' and 'deep' modes with cost and access implications. However, it does not explicitly state when NOT to use this tool or reference sibling tools as alternatives.

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