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

Annotations already mark this as read-only, idempotent, and non-destructive, and the description adds substantial detail beyond that: recomputing capsule_id, picking the schema rule, finding the published batch, recomputing the root, and returning an audit path. It also discloses all possible output states and the semantic limit that verification is proof of publication, not endorsement. 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?

The description is dense and information-rich rather than padded, front-loading the core action and input requirement. The caveat about measurement vs endorsement adds value; the enumerated output states are slightly redundant with the output schema but still useful in a single glance.

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 an output schema, the description is fully sufficient. It covers the input format, the verification algorithm, all result states, cost, and semantic limitations, leaving no critical operational knowledge 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?

The schema covers the single parameter 100%, providing a baseline of 3. The description adds meaningful nuance by explaining that JSON text is preferred for byte-exactness and that number lexemes are preserved, which helps the agent choose the correct input form.

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 opens with a specific verb and resource, 'Verify one measurement capsule', and then defines the exact domain and schema ('csoai.measurement-capsule/0.2'). This distinguishes it clearly from sibling tools like verify_card and verify_inclusion, and it does not merely restate the title.

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 gives clear input guidance: pass capsule_json as byte-exact JSON text or an object. It also explains what verification proves and what it does not prove. However, it does not explicitly contrast this tool with siblings such as verify_inclusion, so the when-to-use-vs-alternative guidance is implicit rather than explicit.

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