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

Annotations already convey read-only, idempotent, and non-destructive behavior. The description adds meaningful context beyond that: signatures cover the exact bytes in `body`, verification is possible offline against a well-known Ed25519 key, and the server need not be trusted. This is valuable behavioral disclosure.

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 states what is returned, the second explains the cryptographic verification mechanism, and the third gives the practical usage trigger. It is front-loaded and contains no filler.

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 single-parameter, read-only tool with no output schema, the description is complete. It explains what the receipts contain, how to verify them, that refusals are included, and when an agent should reach for this 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?

Input schema coverage is 100%, and the only parameter, effect_id, is described directly in the schema. The description adds slight context by emphasizing 'one effect' and 'every decision,' but it does not need to compensate for any schema gaps, so baseline 3 is appropriate.

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 — 'Returns a signed receipt for every decision made about one effect, refusals included.' The mention of signed proof and offline verification clearly distinguishes this from sibling effect-tracking tools like ratchet_report_effect or ratchet_list_effects.

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 explicitly says when to use it: 'Use this when a human asks you to PROVE an action was or was not authorised, rather than asserting it.' It gives a clear trigger condition, though it does not name specific sibling alternatives for the when-not case.

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