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

Annotations cover read-only/idempotent/non-destructive, and the description adds genuinely new behavior: the enforced rule that a number travels with its stage, method, sample and date, that it is never summed across venues/chains/stages, that the URL should be cited rather than this response, and that it errors while the report is unpublished. The 'Read-only.' line merely restates the annotation, hence 4 rather than 5.

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?

Front-loaded with USE WHEN and NOT FOR, then returns, then rules, then example — a well-ordered structure where each block earns its place. Minor waste in presenting RETURNS twice (prose and json), but overall tight and skimmable.

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?

With no output schema, the description carries the full burden and delivers: both return shapes (numbers page payload vs report finding), the field list, an example slug, an error condition, and citation rules. Nothing an agent needs to call and quote it correctly 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 description coverage is 100%: slug (path segment of a satohub.ai/numbers/<slug> URL) and response_format are fully documented in the schema, including the enum. The description restates the slug concept via the URL pattern but adds no syntax or constraints beyond the schema, so the baseline 3 applies.

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 precise verb+resource: it returns the method, sample and reproduce call behind a published Sato Hub number, keyed by slug. It explicitly contrasts itself with onchain_agent_get_agent_economy (fresh measurements) and onchain_agent_get_data_freshness (surface age), so an agent can distinguish it without opening sibling schemas.

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?

Opens with an explicit USE WHEN condition (asking where a published number comes from, needing method/sample/reproduce before quoting) and a NOT FOR clause naming the two alternative tools and the situations that select them. When-to-use, when-not, and alternatives are all present.

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