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

Annotations already cover read-only, idempotent, non-destructive behavior, so the description does not need to restate those. It adds meaningful behavioral detail beyond annotations: the tool returns claims with epistemic classifications, confidence levels, and the units they underpin. It does not describe edge cases or error behavior, but that gap is minor given the safety 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?

The description is two sentences with no redundant words. The first sentence front-loads what the tool does and what each result contains; the second adds a concrete usage rule. Every clause 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?

For a read-only listing tool with a full output schema and complete parameter documentation, the description covers the core behavior, the epistemic categories, the filter option, and the recommended usage timing. Nothing essential for selecting or invoking the tool 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?

Schema coverage is 100%, so the baseline is 3. The description adds value by explaining the meaning of claim_type in context ('to get only what is checkable') and by enumerating the epistemic rungs in prose. Locale semantics are already covered fully in the schema, so no compensation is needed there.

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 the result shape (each tagged with one of four epistemic categories, confidence, and the units they underpin). This clearly distinguishes it from sibling tools like get_claim or list_handbook, which either retrieve a single claim or handle a different resource.

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 explicitly gives a usage context: 'Use this before quoting the handbook to know whether a statement is evidence, a reading of the industry, or a position taken.' It also advises filtering by claim_type to get checkable statements. It does not explicitly name alternatives or when not to use it, but the context is clear enough to guide an agent.

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