Close Recap

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

With no annotations, the description carries the full behavioral burden and does substantial work: it defines an output contract (numbers tagged with dates), discloses that advancers/decliners and sector data have no stable public source and are flagged '未核验' rather than fabricated, states the data source (新浪行情), and declares it gives facts only with no recommendations. This meaningfully exceeds what structured fields provide.

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?

Purpose is front-loaded in the first sentence, followed by the return contract and caveats. Each sentence earns its place (what it returns, how gaps are handled, source, and non-recommendation stance); only the parenthetical skill reference is minor overhead.

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?

An output schema exists, so return values need not be re-explained, and the description still adds the contract, data source and 'no fabrication' caveat. It is nearly complete for a zero-param read tool, with sibling differentiation as the only notable gap.

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 tool takes no parameters (0 params, empty schema), so per the rubric the baseline is 4. There is nothing for the description to disambiguate on the input side.

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?

States a specific verb+resource ('收盘指数快照' - closing snapshot) and enumerates exactly what is returned (涨跌幅/现价/成交量/成交额 for the four major A-share indices). It is clear on its own, but does not explicitly differentiate itself from closely related siblings like 'quote' or 'market_snapshot', leaving some ambiguity about which snapshot tool to pick.

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 mention of '盘后复盘' (after-hours review) implicitly signals the usage context, and the reference to skill 'laogu-close' ties it to a workflow. However, it never states when to use this instead of the overlapping 'quote' or 'market_snapshot' siblings, so the usage rule must be inferred.

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