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

Annotations already declare readOnly, idempotent and non-destructive, so the safety profile is covered. The description adds genuine behavioral context: the ledger is signed, and superseded claims name their replacement, which shapes how the agent should interpret returned entries.

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, no filler, with the resource and the optional filter front-loaded. The topic list is long but carries necessary information that appears nowhere else.

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 whose safety profile is fully covered by annotations, the description covers scope, filtering and one important return-shape nuance. It omits pagination, ordering and result volume, which is a minor gap given no output schema exists.

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 documents the single parameter only as 'Optional topic filter' with no enum, so the description's enumeration of valid topic values adds real semantic value beyond the schema. It does not explain matching behavior (exact vs partial) for the filter.

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?

States a specific verb (List) and resource (claims in the signed Grideōs facts ledger), which cleanly separates it from the singular sibling get_claim. It does not name any sibling explicitly, but the list-vs-get distinction is inferable.

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 optional topic filter implies a browsing/scan use case, but there is no explicit when-to-use guidance, no exclusion, and no routing to alternatives such as get_claim or verify_claim. Usage is left to inference.

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