get_stock_industry

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

With no annotations provided, the description carries the full burden. It discloses key behaviors: it fetches data (read-only implied), handles optional parameters with defaults, and returns a markdown table or error. However, it lacks details on rate limits, authentication needs, data freshness, or error specifics, which are important for a tool with no annotation coverage.

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 well-structured and front-loaded with the core purpose in the first sentence. The Args and Returns sections are clear and efficient, with no redundant information. Every sentence adds value, making it appropriately concise for a tool with two parameters.

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 moderate complexity (2 optional parameters) and no annotations, the description is mostly complete: it explains purpose, parameters, and output. However, it lacks behavioral details like error handling or data sources. The presence of an output schema reduces the need to detail return values, but more context on limitations would enhance completeness.

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 compensate. It adds significant meaning beyond the schema by explaining parameter purposes (e.g., 'stock code' with an example 'sh.600000'), optionality, and default behaviors ('If None, uses the latest available date'). This covers both parameters adequately, though it could specify format constraints more explicitly.

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 specific verbs ('fetches industry classification') and resources ('for a specific stock or all stocks'), distinguishing it from siblings like get_stock_basic_info or get_stock_analysis. It explicitly mentions the scope (single vs. all stocks) and the date parameter, making the purpose unambiguous.

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 usage through parameter descriptions (e.g., 'If None, fetches for all stocks'), but it does not explicitly state when to use this tool versus alternatives like get_stock_basic_info or get_stock_analysis. No exclusions or prerequisites are mentioned, leaving usage context partially inferred.

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