audit_methodology

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

With no annotations, the description carries the full behavioral burden and does disclose meaningful limits: it verifies quote-to-text traceability and explicitly does not scientifically validate labels. However, it omits other behavioral facts an agent needs, such as whether the operation is read-only, what it returns, and how mismatched quotes are reported.

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?

Three short, front-loaded statements with no filler; the core purpose leads and the caveats follow. The fragmented line breaks are mildly awkward but do not impede comprehension.

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?

For a tool with five required parameters, an untyped nested annotations array, no output schema, and no annotations, the description is under-specified. While the scope-limiting caveats are useful, an agent still lacks parameter semantics and any sense of the return shape needed to call it correctly.

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% across five required parameters, so the description must compensate but largely does not. It loosely maps to a few fields ('outcome-specific', 'user-annotated', 'supplied raw text') but gives no meaning for study_id or study_design and no format for the annotations array, leaving most parameters undocumented.

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?

States a specific verb (audit) and resource (traceability of methods evidence, with quotes checked against raw text), so the agent knows this is a traceability-verification tool rather than a validity assessor. It does not, however, distinguish itself explicitly from close siblings like audit_pmc_methodology or assess_methodology, leaving that separation to inference.

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 carves out a clear boundary ('Quotes are checked against supplied raw text', 'Labels are never scientifically validated'), which implicitly tells the agent this is a limited scope-check rather than a full appraisal. But it never states when to choose this over audit_pmc_methodology or assess_methodology, nor any prerequisites, so usage is only implied.

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