stock_concept_cons_futu

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

Annotations already declare the full safety profile (readOnly, idempotent, open-world, non-destructive), so the bar is lowered. The description usefully discloses the data provider and that the return is a pandas.DataFrame, but adds nothing about rate limits, freshness, or data 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 docstring is compact and front-loads the resource name, then gives the param, type and return type. Every line is functional, though the bare URL is only marginally useful.

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 single-parameter read-only tool with no output schema, the description covers the resource, source, accepted values and return type, and annotations cover safety. Only the exact columns/scope of the returned DataFrame remain unspecified.

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?

Schema description coverage is 0% and the schema declares no enum, so the description carries the parameter burden. It compensates by enumerating the valid symbol values (巴菲特持仓, 佩洛西持仓, 特朗普概念股), which is essential information absent from the schema.

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 names a specific resource (概念板块成分股 = concept-sector constituent stocks) and its source (富途牛牛/主题投资, with a URL). It is clear what data is returned, though there is no explicit verb and no differentiation from similar siblings such as stock_board_concept_cons_em.

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?

There is no statement of when to use this tool versus alternatives, and the many sibling concept/board tools (e.g. stock_board_concept_cons_em, stock_board_concept_name_em) are never mentioned. Usage is only implied by the topic description.

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