verify_turn

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

Despite no annotations, the description thoroughly discloses behavioral traits: it checks claims against 'indexed repo + working-tree git diff + logs', returns 'cited supported / contradicted / refused verdicts', is deterministic, and 'refused' means unverifiable. It also warns that listing a claim cannot make it pass.

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 somewhat lengthy but well-structured with a clear purpose statement followed by a 'HOW TO CALL' section. Every sentence contributes critical guidance, though a slight tightening could improve conciseness. Overall, it's efficient for the amount of information conveyed.

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 4 parameters, 100% schema coverage, no output schema, and no siblings, the description is remarkably complete. It covers purpose, usage, behavioral details, parameter semantics, and even explains the deterministic nature and verdict types. The agent has all the information needed to use the tool 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 100%, which sets a baseline of 3. The description adds significant value by explaining the rationale behind each parameter: `claims` is recommended and self-extracted, `message` is a backstop, `repo` is strongly recommended, and `local_log` is optional. It clarifies how to use them effectively.

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 explicitly states the tool's purpose: 'Fact-check your own claims about code you changed, BEFORE telling the user a change is done — to catch over-claims'. It specifies the verb (fact-check), the resource (claims about code changes), and the timing (before telling the user). This clearly distinguishes it from any potential sibling tools.

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 provides clear guidelines on when to use the tool ('BEFORE telling the user a change is done') and how to use it (extract concrete factual claims, pass them in `claims`, always include `message` as backstop). It does not explicitly mention when not to use it or alternatives, but the context is strong.

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