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

Although no annotations are provided, the description discloses a key behavioral trait: cost ($0.01). It also mentions output includes filing provenance and quality flags, which is useful for the agent. It does not cover authentication or rate limits but adds significant value beyond empty 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 a single, well-structured sentence that front-loads the key information. Every word serves a purpose with no redundancy or unnecessary detail.

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?

While the output schema exists to cover return structure, the description omits explanation of temporal filtering (fy_from) and pagination (limit), which are relevant for correct usage. The main use case is covered, but gaps remain.

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 description adds concrete examples for the 'concept' parameter (e.g., revenue, net_income) which is not in the schema. However, it does not explain 'limit', 'fy_from', or 'cik'. With 0% schema description coverage, this partial compensation is notable.

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 clearly states it returns 'raw normalized XBRL facts' and mentions filtering by canonical concept, distinguishing it from sibling tools like company_filings or company_financials which handle filings or processed data.

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 implies usage for raw XBRL fact retrieval with filtering but does not explicitly state when to use this tool versus alternatives or provide exclusion criteria. The sibling list provides context, but the description lacks explicit guidance.

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