get_cash_flow_data

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

No annotations are provided, so the description carries full burden. It mentions the return format ('Markdown table with cash flow data or an error message'), which adds some behavioral context. However, it lacks details on permissions, rate limits, data freshness, or error conditions, which are important for a data-fetching 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 with clear sections (purpose, Args, Returns) and uses bullet-like formatting. It's appropriately sized with no redundant information, though the 'Args' and 'Returns' labels are slightly verbose compared to a more streamlined approach.

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 (3 parameters, no annotations, but has an output schema), the description is fairly complete. It covers the purpose, parameters with examples, and return format. The output schema existence means the description doesn't need to detail return values, but it could benefit from more behavioral context (e.g., error handling, data sources).

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?

The description adds significant meaning beyond the input schema, which has 0% description coverage. It explains each parameter's purpose and provides examples (e.g., 'code: The stock code (e.g., 'sh.600000')', 'year: The 4-digit year (e.g., '2023')', 'quarter: The quarter (1, 2, 3, or 4)'), fully compensating for the schema's lack of documentation.

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 'fetches quarterly cash flow data for a stock' with a specific example ('CFO/Operating Revenue ratio'), which is a clear verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'get_hk_cash_flow_data' or 'get_balance_data', which appear to fetch similar financial data for different markets or types.

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 provides no guidance on when to use this tool versus alternatives. With many sibling tools for financial data (e.g., 'get_hk_cash_flow_data', 'get_balance_data', 'get_profit_data'), there's no indication of context, prerequisites, or exclusions to help an agent choose appropriately.

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