Earnings Analysis

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It compensates well for the missing output schema by listing return values (verdict, beat rate, trajectory, summary), but fails to disclose operational traits like safety profile, idempotency, data freshness, or rate limits.

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 consists of two highly efficient sentences. The first front-loads the action and scope (earnings analysis), while the second discloses output format. No words are wasted.

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 simple single-parameter tool without output schema, the description adequately covers the tool's purpose and return structure. It could be improved by mentioning data sources or freshness, but it meets the minimum requirements for agent selection.

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 for the single 'ticker' parameter. The description does not explicitly discuss the parameter, but since the schema fully documents it, 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 analyzes a stock's earnings track record, specifying EPS beat/miss history and revenue trends. While it effectively distinguishes itself from general stock analysis tools like 'stock_thesis' or 'valuation_snapshot' through specific focus areas, it does not explicitly name siblings for differentiation.

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 mentions the analysis is for 'long-term investors,' implying a use case, but provides no explicit guidance on when to use this tool versus alternatives like 'stock_thesis' or 'valuation_snapshot,' nor does it state prerequisites or exclusions.

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