List the corpus claims and their epistemic status

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

Annotations already declare readOnlyHint=true and idempotentHint=true, covering the safety profile. The description adds useful behavioral context: claims carry confidence and underpinned units, are categorized by epistemic rung, and claim_type filtering narrows to checkable statements. No contradiction with 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, each earning its place: the first defines what the tool returns, the second explains when to use it, the third gives filtering guidance. Front-loaded with the core verb and resource.

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 read-only list tool with two optional enum parameters and an output schema, the description plus annotations fully cover purpose, usage, and parameter behavior. Nothing an agent needs to call it correctly is missing.

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?

Both parameters are fully documented in the schema with enums and descriptions, so schema coverage is 100%. The description adds a small semantic nuance ('claim_type' returns only what is checkable) but does not need to compensate for any schema gaps.

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 ('List'), a specific resource ('load-bearing claims of the corpus'), and enumerates the exact tag types returned. This clearly distinguishes it from sibling tools like list_handbook or get_claim.

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?

It gives an explicit use-case ('Use this before quoting the handbook') and explains the value of filtering by claim_type to scope to checkable claims. It does not name alternatives or exclusions, but the context is sufficient for correct selection among siblings.

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