stock_board_concept_cons_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 cover the safety profile. The description adds the return type (pandas.DataFrame) and parameter meaning, but provides no extra context about data freshness, limitations, or behavior beyond that.

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 and well-structured: title, source URL, and docstring parameters. Each line contributes value, and there is no redundant text.

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?

With one parameter and rich annotations, the description covers the core aspects: what the tool returns and the parameter meaning. It could be more complete by listing example board names or DataFrame columns, but these are minor omissions for a simple read-only tool.

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 0% description coverage for the 'symbol' parameter, but the description explains it accepts a board name or code, adding essential meaning. It does not provide format examples, but the default value and type are clear.

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 identifies the tool's purpose as retrieving '板块成份' (board constituents) for EastMoney Shanghai/Shenzhen concept boards, with a source URL and Python-style docstring. This distinguishes it from sibling tools like spot data or historical data retrievers.

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 about when to use this tool versus alternatives. It does not mention sibling tools, exclusions, or prerequisites, leaving the usage context to be inferred purely from the tool name.

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