Analyze Company Financials

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

The annotations already reveal read-only and non-destructive behavior, so the description adds value by explaining the interpretative nature of the tool—computing ratios, scores, and trend detection. This goes beyond the safety profile provided by annotations, enhancing the agent's understanding of what to expect.

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 sentences long, packed with specific, relevant details and a clear differentiator. Every phrase adds value, and the structure is front-loaded with the most important information, making it efficient and easy to parse.

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?

Since there is no output schema, the description carries the burden of explaining return values, and it does so by listing concrete metrics and the composite health grade. It does not detail the exact structure or mention potential raw data inclusion, but for a single-parameter read-only tool, this is largely sufficient.

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 fully documents the single parameter (cik) with 100% coverage, so the description does not need to add parameter details. The description does not elaborate on cik beyond the schema, so the baseline score of 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?

The description clearly states the tool's purpose with a specific verb ('analyze') and resource ('company financials'), while listing concrete outputs such as profit margins, ROE, ROA, growth metrics, and a health grade. This distinguishes it from sibling tools like get_financial_metric, which likely return single raw metrics.

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 that this tool is for comprehensive, interpreted analysis rather than raw data, as stated by 'This goes beyond raw data — it interprets the numbers.' However, it does not explicitly name alternative tools or state exclusions, providing clear context but not full when/when-not guidance.

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