yupao_record_match

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

Annotations already declare a non-read-only, non-destructive, closed-world write. The description usefully adds that validation of citations occurs and that 'unknown' is distinct from 'not satisfied' — real behavioral context. It does not say what happens when validation fails (reject, repair, or store anyway) or whether re-recording overwrites prior analysis, which are the biggest open questions for a write tool.

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?

A single dense sentence that front-loads the action and then the processing behaviors. Nothing is wasted, though the two clauses are separated only by a semicolon, making it easy to skim past the behavioral detail.

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?

Given a nested, undocumented object payload, no output schema, and only 0% schema coverage, the description should define the analysis object's expected contents and the validation outcome. It hints at these but leaves an agent unable to call the tool correctly without trial and error.

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 core parameter `analysis` is a free-form nested object with additionalProperties:true, so the schema provides essentially no guidance. The description gestures at the payload's semantics (per-item analysis, citations, unknown vs unmet, weighted aggregation) but gives no field names or structure, leaving the agent to guess the object shape.

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 gives a concrete verb+resource: persisting the host AI's item-by-item match analysis, plus the extra processing it performs (validating JD/resume citations, separating unknown from unmet, aggregating weights). This separates it from yupao_list_matches and yupao_prepare_match, though it never names those siblings explicitly.

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 phrase '宿主 AI 的逐项匹配分析' implies it is called after analysis has been produced (i.e., downstream of yupao_prepare_match), but no when/when-not condition or alternative is stated. An agent can infer the lifecycle position but not the boundaries.

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