compare_industry_valuation

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

With no annotations provided, the description fully discloses behavioral traits: raises NoDataFoundError for missing data, lists skipped peers with reasons, excludes target from statistics, and uses trimmed mean. All critical behaviors are 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 concise yet comprehensive, with a front-loaded purpose statement and a well-organized behavior contract. It uses markdown-style headings and bullet points, making it easy to parse. Every sentence adds value.

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?

Given the tool's simplicity (2 parameters, no output schema), the description is complete: it covers input semantics, error conditions, peer coverage output, and statistical methodology. No gaps remain.

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%, so the description must add meaning. It explains 'code' as the target stock code, 'date' as comparison date with format and default behavior ('YYYY-MM-DD' and defaults to latest). This fully compensates for the lack of schema descriptions.

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: compare a stock's valuation (PE/PB/PS) against industry peers. The verb 'compare' and resource 'valuation' are specific, and the function distinguishes itself from siblings like get_valuation_metrics or calculate_dcf_valuation by focusing on peer 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 description includes a detailed behavior contract explaining when errors occur and how peer coverage is handled. It implicitly guides usage for stocks with industry classification and data availability, but does not explicitly direct when to use this tool over alternatives.

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