Get company data availability and freshness

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

Annotations already cover read-only/safety, and the description adds real behavioral context beyond them: it is 'cheap' (cost signal), reads only indexed metadata rather than live research endpoints, never triggers enrichment, and explicitly warns that availability != completeness/accuracy and that a null timestamp means unknown freshness. These are caveats an agent could not infer from the schema.

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?

Dense but front-loaded: the manifest contents lead, then usage guidance, then caveats. Almost every sentence carries distinct information; 'Read-only' merely restates the annotation and 'cheap' is an unquantified adjective, minor waste.

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 successfully doubles as a return-value specification by enumerating the fields the manifest exposes. Combined with the freshness caveats and the single well-documented parameter, an agent has everything needed to call it and interpret the result.

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 coverage is 100% and the ticker parameter already documents formats and the search_stocks fallback. The description only reinforces the 'one exact company' scope, adding no syntax or constraint detail beyond the schema, so the 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?

States a specific resource ('stored-data manifest for one exact company') and enumerates exactly what it contains: available datasets, latest reporting periods, ingestion/computation timestamps, and cached relationship graph status. The line 'This reads indexed metadata, not every research endpoint' cleanly separates it from sibling data tools like get_financial_history or get_company_relationships.

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?

'Call before deeper research when coverage or freshness is uncertain' gives a concrete trigger condition, and 'never starts enrichment' bounds the action. It stops short of naming a specific alternative tool to use instead when coverage IS known, so routing is implied rather than explicit.

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