compare_stocks

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

No annotations are provided, so the description carries the transparency burden. It discloses that the output is an LLM-generated conclusion, which is a notable behavioral trait, and mentions default core financial indicators. However, it does not cover limitations, permission requirements, or output structure.

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 two short paragraphs, front-loading the purpose and then listing parameters. Every sentence earns its place with no redundancy.

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?

The tool is simple (2 params), and the description covers purpose, parameters, and output nature. However, without an output schema, it could further specify the structure of the comparison conclusion or constraints on the number of symbols, leaving a small gap.

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 descriptions are absent (0% coverage), but the description explains both parameters: symbols as a list of codes/names with an example, and metrics as optional English keys with default behavior. This adds essential meaning beyond the bare schema, though valid metric keys are not enumerated.

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 compares key indicators of multiple A-share stocks and returns LLM-generated conclusions. This distinguishes it from sibling tools like analyze_stock (single stock analysis) and stock_report (single stock report).

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 for multi-stock comparison but does not explicitly state when to use this tool over alternatives. No when-not conditions or alternative tool names are mentioned.

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