Extract claims to verify

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

Annotations already establish read-only, idempotent, non-destructive, and closed-world behavior. The description adds useful behavioral context beyond that: discovery is deterministic while judgment is delegated to the LLM/caller, which clarifies the tool's role in the verification workflow.

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 are front-loaded and efficient. The first states the action and output; the second adds the key behavioral split in one compact clause.

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?

No output schema exists, so the description should convey the return shape. It does so at a high level (a verification task list) and explains the caller's follow-up role. More detail on the task-list structure could help, but the definition is adequate for a one-parameter read-only tool.

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?

There is one optional parameter with 100% schema description coverage. The schema fully documents projectDir, its default, and scope, so the description does not need to repeat it; baseline 3 is appropriate because the description adds no parameter semantics beyond the schema.

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: extract semantic claims (documented numbers, limits, enums) from canonical docs as a verification task list. It is clear what the tool does, but it does not explicitly distinguish this from sibling tools such as docguard_verify_evidence or docguard_diagnose.

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?

Usage is implied as a discovery step before verification: the caller verifies each extracted claim against the code. There is no explicit when-to-use guidance, no when-not-to-use guidance, and no named alternatives among the sibling tools.

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