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

Beyond the readOnlyHint and idempotentHint annotations, the description adds important behavior: figures are served as filed (no adjustments), except derived figures which are calculated and explained. It also clarifies that a missing period means 'nothing filed', not zero. This is valuable context on data provenance and interpretation. Slight deduction because it doesn't mention rate limits or error cases, but it's strong.

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, dense paragraph but is well-structured: it starts with the core purpose, then input specifics, then data semantics. It's front-loaded with the purpose. All sentences add value, but it could be broken into bullet points for easier scanning, hence 4 rather than 5.

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?

Given the tool is simple (one parameter, annotations for read-only/idempotent) and the schema is fully descriptive of the parameter, the description covers the essential semantics: data ordering, source citations, derived figures, and missing period handling. It doesn't describe the output structure but no output schema is provided; however, the nature of financial figures is understandable. It's complete enough for an agent to call correctly.

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?

Although the schema already describes node_id as the graph node id from search_companies (100% coverage), the description reinforces the distinction from company_profile's entity_id and explains the source of the id. This adds clarity beyond the schema, making it more than just a baseline 3.

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 provides financial figures for a single company, ordered by reporting period, with source citations. It distinguishes itself from siblings like company_profile by focusing on financials, and from search_companies by being a per-company data tool rather than a search tool. However, it does not explicitly name a sibling for contrast, so it falls short of a 5.

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?

It explicitly tells the agent when to use this tool: when financial figures for one company are needed, and it gives a precise input instruction: use node_id from search_companies, not entity_id from company_profile. This is a clear when-to-use and what-not-to-use, which is excellent.

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