list_applications

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

No annotations are provided, so the description carries the full burden. It discloses key behavioral traits: it's a read-only operation (implied by '查看' - view), returns specific data fields (candidate info, match scores, badges, status, cover letters), includes match score interpretation guidelines, and notes pagination support (via page/page_size parameters). However, it lacks details on authentication needs, rate limits, error handling, or data freshness.

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 well-structured and appropriately sized. It front-loads the core purpose, then lists return information, explains match scores, and adds a note about limitations. Most sentences earn their place by providing useful context, though the match score breakdown could be slightly condensed.

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 no annotations and no output schema, the description does a fair job covering the tool's behavior, return data, and limitations. It explains what data is returned and how to interpret match scores, which compensates for the lack of output schema. However, for a tool with 5 parameters and no annotations, it could benefit from more details on error cases, authentication, or performance characteristics.

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 100%, so the schema already documents all parameters thoroughly. The description doesn't add any parameter-specific semantics beyond what's in the schema (e.g., it doesn't explain 'job_token' or 'status' enums further). However, it implicitly references pagination via 'page' and 'page_size' by listing them as returned data, which slightly reinforces their purpose. Baseline 3 is appropriate given high schema coverage.

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 states the tool's purpose: '查看收到的职位申请' (view received job applications). It specifies the verb (view) and resource (job applications), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'view_candidate' or 'search_candidates', which might also involve viewing candidate-related data.

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 usage context by stating it's for viewing applications and noting that processing applications (approve/reject) will be in v2, suggesting this is for read-only inspection. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like 'search_candidates' or 'view_candidate', nor does it mention prerequisites (e.g., needing a session_id from 'register_company').

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