stock_vs_industry

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

No annotations are provided, so the description carries the behavioral disclosure burden. It discloses the data source (Finviz), the temporal nature ('current snapshot'), and the output shape (absolute stock value, industry median, and delta for each metric). It does not mention auth, rate limits, or invalid-ticker behavior, but for a read-only retrieval tool this is reasonably transparent.

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 front-loaded with the main purpose, then lists metric categories, output elements, data source, and the single argument. It is compact and every sentence contributes useful information, though the metric-category list adds some length without being essential.

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 one-parameter tool with an output schema, the description covers the use case, metrics, output structure, data source, and ticker argument. It lacks explicit usage-vs-alternatives guidance and caveats about snapshot freshness beyond 'current snapshot', but it is complete enough for an agent to invoke the tool 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?

Schema description coverage is 0% and the schema only labels the parameter as 'Ticker'. The description compensates by defining the parameter as a stock ticker symbol and providing concrete examples including 'BRK-B', which signals how to format tickers. This adds real meaning beyond the schema.

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 opens with a specific verb and resource: 'Get a stock's valuation and fundamentals relative to its industry.' It clearly distinguishes the tool from siblings like compare_stocks (peer comparison) and compare_industries (industry aggregates) by emphasizing stock-to-industry comparison.

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 use case is implied clearly: use this when you need a stock's metrics against its industry. However, there is no explicit guidance about when not to use it or which alternative tools to prefer for peer-stock comparison, industry-only aggregates, or screening. The context is present but exclusions and alternatives are left to the agent to infer.

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