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

Annotations already declare readOnlyHint/openWorldHint=false, but the description adds genuinely new behavioral context: it is cheap, it does not trigger enrichment, availability is not completeness or accuracy, a null timestamp means freshness is unknown, and a reporting period is not an ingestion date. These caveats directly prevent misinterpretation of the returned manifest.

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 the resource and its contents, then the usage rule, then caveats. No sentence is filler — each clause either scopes the tool or prevents a specific misreading of its output.

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 burden of describing returns and does so (datasets, periods, timestamps, graph status), plus it flags freshness/accuracy caveats. Nothing an agent needs to invoke it correctly or interpret results 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% and the single ticker parameter is documented in extensive detail (examples, suffix behavior, fallback advice) in the schema itself. The description adds nothing about the ticker beyond 'one exact company', so 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?

States a specific verb and resource ('cheap stored-data manifest for one exact company') and enumerates exactly what it returns: available datasets, latest reporting periods, ingestion/computation timestamps, cached relationship graph status. It also explicitly delineates itself from deeper research endpoints, so an agent can distinguish it from siblings like get_stock_metrics 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 clear triggering condition, and 'never starts enrichment' plus 'reads indexed metadata, not every research endpoint' bound the scope. It stops short of naming specific alternative tools, which keeps it below a 5.

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