日历-关联领域成分股(实时)

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

With no annotations at all, the description carries the full transparency burden and does meaningful work: it discloses the time-dependent behavior (盘中实时 vs 最近交易日收盘) and names the data provider (腾讯). This is exactly the kind of behavioral trait an agent needs to interpret results correctly. It stops short of covering failure modes or what 'auto' mode resolves to, but the core behavioral disclosure is strong.

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?

Two tight sentences: core function first, then source/mode behavior, then return format. No filler or repeated title content. The return-format snippet is slightly dense but earns its place since there is no output schema to reference.

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 3-parameter tool with zero annotations, 0% schema coverage, and no output schema, the description leaves major gaps: parameter semantics are entirely absent, and there is no statement about what happens with an empty domain or how the domain string is matched. The return-shape disclosure helps, but an agent would still be guessing on how to fill in dtype and domain.

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%, yet the description explains none of the three parameters. 'domain' (what string to pass, how it matches a domain), 'dtype' (what values it accepts, what 'auto' means), and 'limit' (max count? pagination?) are all opaque. At zero schema coverage, the description was obligated to compensate and did not.

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 specifies a clear verb+resource+outcome: parse associated domains (概念/行业/板块) into constituent stocks, with a concrete data source (Tencent) and return shape. It is reasonably distinguishable from siblings like industry_sw_constituents and stock_concepts by its domain-agnostic scope (concept/industry/sector) and real-time/close mode, though it never explicitly names a competing sibling.

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 implies when to use the tool: during trading hours it returns real-time snapshots, after close it returns the latest close. This gives context on invocation timing, but provides no explicit guidance on when not to use it or which alternatives (e.g., industry_sw_constituents for strict SW-industry constituents) to choose instead.

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