scan_to_excel

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

No annotations are provided, so the description bears full responsibility for behavioral transparency. It mentions max 500 codes and the caching pattern, but lacks details on file overwriting behavior, error handling, performance implications, or any prerequisite permissions.

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 (5 sentences) and well-structured: a headline summary, a workflow note, and a bulleted list of parameters. Every sentence adds value without 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?

Given the tool's complexity (multiple data types, Excel output, caching pattern and an output schema present), the description covers the essential aspects: purpose, workflow, parameters. It could briefly mention the return value (file path) or limitations, but overall it is sufficiently complete for an AI agent to use effectively.

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 provides clear, concise explanations for all four parameters in the 'Args' section, directly addressing the 0% schema description coverage. Each parameter's meaning, default value, and constraints are covered (e.g., codes max 500, days default 260 weeks, include_financial toggle, filename auto-generation).

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: scanning multiple stocks to collect basic info, chart statistics, and financial indicators and saving to Excel. It also introduces the local cache pattern for repeated filtering via query_excel, distinguishing it from sibling tools that retrieve data without saving to files.

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 explicitly outlines the workflow: scan first, then use query_excel for filtering. This gives clear usage guidance. However, it does not directly state when not to use this tool or mention alternatives among siblings, such as get_multi_stocks for in-memory data.

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