Generate mock interview questions and preparation advice from a target job description, optionally using a resume to tailor questions for candidate practice.
基于目标职位描述生成模拟面试题与准备建议（支持简历参考定制题目） [可用性: roles=candidate; candidate_platforms=zhipin; recruiter_platforms=-]
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | 题量，默认 10 | |
| resume | No | 参考简历名称（可选） | |
| jd_text | Yes | 目标职位描述文本 |
Changes observed during successful MCP inspections.
v1.19.1v1.18.0v1.17.0v1.16.0v1.11.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are supplied, so the description carries the burden. It usefully discloses the role/platform availability constraint, which is genuine behavioral context. But it says nothing about whether generation is safe/non-mutating, latency, rate limits, or what the output looks like.
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?
Single front-loaded sentence plus a bracketed availability tag; no wasted wording. The bracketed constraint is compact though somewhat cryptic in format.
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 generation tool with no output schema and no annotations, the description covers purpose and availability but leaves the return shape (number/format of questions, advice) and any safety profile unstated. Adequate but with clear gaps.
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 baseline is 3. The description does add that supplying a resume customizes the generated questions, which clarifies the purpose of the optional resume param beyond the schema's '参考简历名称'. Marginal added value.
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 and resource: generates mock interview questions and preparation advice from a target JD, with optional resume-based customization. Clear on its own, but it doesn't differentiate from adjacent AI siblings like boss_ai_fit or boss_ai_chat_coach.
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 availability line (roles=candidate; candidate_platforms=zhipin) gives real gating context, and 'based on target job description' implies when it applies. However, there is no explicit when-not guidance or naming of alternative tools such as boss_ai_fit for prepping differently.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.