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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context beyond annotations: it is a premium API with a specific cost ($0.25 USDC via x402), which is critical for an agent deciding whether to invoke it. It also clarifies the output is AI-powered analysis, not just raw data.

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?

Two sentences with zero waste. The core purpose is front-loaded, the return fields are listed compactly, and the premium/cost warning is placed at the end. Every sentence 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 single-parameter read-only tool with 100% schema coverage and no output schema, the description is nearly complete. It covers what the tool does, what data it returns, and the cost implication. The only minor gap is that it doesn't describe the return format or error behavior (e.g., invalid ticker), but the annotations and simple parameter schema make this a minor omission.

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?

Schema description coverage is 100%, so the schema already documents the single 'lookup' parameter with examples and a clear description. The tool description adds the context that the lookup is a ticker symbol and that the analysis is AI-powered, but it does not add new parameter-level semantics beyond what the schema provides. Baseline 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 states a specific verb ('Get'), a specific resource ('AI-powered stock analysis for a ticker symbol'), and enumerates the exact data fields returned (price, market cap, P/E ratio, EPS, analyst assessment). This clearly distinguishes it from the many sibling tools, which cover addresses, companies, weather, etc.

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 the tool is for stock ticker lookups and the input schema clarifies the lookup parameter, but it does not explicitly state when to use this tool versus alternatives or mention any exclusions (e.g., unsupported tickers, delisted stocks). The context is clear enough for an agent to select it for stock-related queries, but no explicit when/when-not guidance is given.

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