stock_board_industry_hist_min_em

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which establish the safety profile. The description adds the return type (pandas.DataFrame) and the concrete data source URL, but does not disclose any other behavior such as possible missing data, refresh delays, or what happens for invalid sector names. This is acceptable but minimal given the 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 short and front-loaded with the purpose line, then a URL and parameter definitions. It is tight and free of fluff, though the inclusion of a raw URL might be seen as non-essential for an automated agent. Overall, it earns its place in a compact format.

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?

For a 2-parameter tool with no output schema, the description is incomplete. It fails to mention the available time range, data granularity (e.g., 1-minute against which trading sessions), or any example usage. It also lacks a pointer to companion tools for obtaining sector symbols (e.g., stock_board_industry_name_em), which are critical for successful invocation.

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 schema has no descriptions (0% coverage), so the description carries the burden. It does explain symbol as '板块名称' (sector name) and period as allowed choices {'1','5','15','30','60'}, which provides crucial meaning. However, it does not specify exact expected format (e.g., Chinese sector names only) or how to discover valid symbols, leaving the agent partially informed.

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 resource (Eastmoney industry boards) and action (retrieve minute-level historical quotes) with the exact data source URL. The term '分时历史行情' explicitly distinguishes this from same-sector daily history (stock_board_industry_hist_em) and spot data (stock_board_industry_spot_em) siblings.

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?

No guidance is provided on when to use this tool versus alternatives. The description only lists parameters and the return type, with no mention of trade-offs, prerequisites (e.g., obtaining sector names via name-list tools), or exclusions. This leaves the agent to infer usage solely from the name.

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