get_balance_data

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

No annotations are provided, so the description carries the full burden. It states the tool 'fetches' data and returns a 'Markdown table with balance sheet data or an error message,' which implies a read-only operation with potential errors. However, it lacks details on permissions, rate limits, data freshness, or what specific metrics (beyond examples like current ratio) are included. For a financial data tool with no annotations, this is insufficient.

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 appropriately sized. It starts with a clear purpose sentence, followed by 'Args:' and 'Returns:' sections that efficiently document parameters and output. Each sentence adds value without redundancy, though the 'Args:' and 'Returns:' labels are slightly verbose compared to a more integrated 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, financial data fetching), no annotations, and an output schema (implied by 'Returns:' but not detailed), the description is partially complete. It covers parameters well and mentions the output format, but lacks behavioral details (e.g., error conditions, data sources). With no annotations and an output schema that likely defines the table structure, the description should do more to explain operational context.

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: 'code' as 'The stock code (e.g., 'sh.600000')', 'year' as 'The 4-digit year (e.g., '2023')', and 'quarter' as 'The quarter (1, 2, 3, or 4)'. This clarifies formats and constraints (e.g., quarter values), compensating fully for the schema's lack of 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: 'Fetches quarterly balance sheet / solvency data (e.g., current ratio, debt ratio) for a stock.' It specifies the verb ('fetches'), resource ('balance sheet / solvency data'), and scope ('quarterly', 'for a stock'). However, it doesn't explicitly differentiate from sibling tools like 'get_cash_flow_data' or 'get_profit_data', which likely fetch different financial statement 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. It doesn't mention sibling tools (e.g., 'get_cash_flow_data' for cash flow statements, 'get_profit_data' for income statements) or specify scenarios where balance sheet data is preferred. Usage is implied through the description but not explicitly stated.

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