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

Beyond the annotations' readOnlyHint/idempotentHint, the description discloses important behaviors: it enforces a provenance rule (numbers never aggregated across venues/chains/stages), returns an error while unpublished, and requires the payload URL to be cited. This adds context about output integrity and answer format that the annotations do not provide.

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 front-loaded with a one-sentence purpose, then gives the key behavioral rules, output shape, and a concrete example. It is more verbose than minimal but every section earns its place, especially the return-list since there is no output schema. The uppercase stylistic choices are mildly noisy but not wasteful.

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?

Since there is no output schema, the description compensates by enumerating the JSON return fields (slug, title, number, unit, stage, method, sample, lines, query, as_of, url, cite, rules) and giving an example call. It also covers unpublished-report behavior and read-only status, making the tool reasonably complete for independent invocation.

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 description coverage is 100% and already explains the slug as a URL path segment and response_format as an enum with a default. The description adds a helpful example slug and reiterates the slug-shape URL, but it does not meaningfully elaborate on the parameters beyond the schema. 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-resource relationship: it answers where a published Sato Hub number comes from and returns one finding by slug. It gives clear distinctions from broad sibling tools like search_agents or get_metrics, focusing on provenance metadata for a single slug.

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?

Usage is implied rather than explicit: the example and slug input set up the intended invocation, and the error-while-unpublished note gives a temporal constraint. However, there is no clear when-to-use-versus-alternatives guidance or named sibling exclusions, so an agent must infer when this tool is preferred over similar lookups.

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