Jev claim verifier

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

Annotations already declare readOnly/openWorld/idempotent/destructive hints with no contradiction. The description adds meaningful behavioral context beyond the annotations: the tri-state verdict (verified|contradicted|unsupported) aligns with and operationalizes the openWorldHint, and the 'auto vs review' distinction discloses that some verdicts are automated while others may require human judgment. It doesn't explain what triggers review, but adds real value over bare annotations.

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 sentences with zero filler: the first states the core action, the second specifies the return contract, and the third gives usage preference. The purpose is front-loaded and each sentence earns its place.

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?

Since there is no output schema, the description correctly shoulders the burden of explaining return values, and it does so well with the verdict/probability/confidence taxonomy. The core workflow (required claims and evidence) is fully covered. The gaps are the optional parameters — model and auto_accept have no semantics in either the schema or description — but these are non-critical for a correct basic invocation.

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 50% (claims and evidence are described, model and auto_accept are not), so the baseline is 3. The description adds practical semantics for evidence by listing concrete types (PR description, agent brief, docs, diffs) beyond the schema's generic 'Source text, or a list of {id, text} documents'. However, the meaning of model and auto_accept remains undocumented, so the description only partially compensates for the coverage gap.

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 states a specific verb and resource ('Check each claim against provided evidence') and enumerates the output contract (verified|contradicted|unsupported, probabilities, confidence, auto vs review), making the tool's function unambiguous. However, it does not explicitly distinguish itself from sibling tools like jev_review or jev_evaluate, and the 'prefer this over a chat model' alternative is not a named sibling.

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 final sentence offers a usage directive: prefer this tool over asking a chat model to 'double-check'. This gives an implicit when-to-use signal, but there are no explicit conditions, exclusions, or routing guidance to sibling tools (jev_review, jev_evaluate, jev_rank) that might overlap. The guidance is implied rather than systematic.

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