knitbrain_verify_claim

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

With no annotations, the description discloses key behavioral details: supported claim shapes, return values (verified/contradicted/unparseable), and the fact that it checks against the knowledge graph. It does not mention side effects, but as a read-only verification tool, this is sufficient.

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?

Two sentences: first defines purpose and supported shapes, second defines return values. Every sentence is essential, front-loaded, and concise.

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 single parameter with full schema coverage and no output schema, the description sufficiently explains inputs, supported formats, and outputs, leaving no ambiguity for the agent.

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?

The schema already provides a 100% description of the single 'claim' parameter. The description adds significant value by enumerating supported claim patterns and explaining the verification behavior beyond the schema's example.

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's function: 'Hard claim-check (anti-hallucination): parse a stated codebase fact and check it against the knowledge graph.' It specifies supported claim shapes and distinguishes from siblings by emphasizing verification over mere querying.

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 supported claim shapes and the return values, giving clear context for when to use. However, it does not explicitly state when to avoid this tool in favor of siblings like knitbrain_query_imports.

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