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

The description adds significant behavioral context beyond the annotations by disclosing the sorting order ('newest first'), the data granularity ('one row per fiscal year'), and the specific data points returned. It also clarifies data encoding ('Amounts are EUR CENTS as integers') which is crucial for correct processing. While annotations cover safety, the description carries the burden of explaining the return structure and data format well.

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 two concise sentences with zero waste. It is front-loaded with the core purpose and data structure, followed immediately by the crucial usage guideline and the alternative tool. Every clause is informative and earns its place.

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?

For a read-only, idempotent tool with a fully described schema and an output schema, the description is complete. It covers the purpose, the return format (rows, sorting, fields, currency units), and the primary routing decision against a sibling tool. No critical information for a correct invocation 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?

The input schema has 100% description coverage, fully documenting the 'ico', 'years', 'country', and 'purpose' parameters. The description does not repeat this schema information but instead focuses on output and usage, which is appropriate. The schema does the heavy lifting for parameters, warranting a baseline score.

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 specific verb and resource ('Filed financial statements of one company') and specifies granularity ('one row per fiscal year'). It explicitly distinguishes itself from the sibling tool company_brief by stating 'company_brief already carries the latest year,' clearly delineating the scope of this tool.

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 provides explicit guidance on when to use the tool ('Use for trend and solvency questions') and names the alternative ('company_brief') along with the condition that selects it (it 'already carries the latest year'). This leaves no ambiguity about which tool to choose for historical data.

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