模拟面试会话列表
mock_interview_listList past mock interview sessions with progress and status so you can track practice history and identify areas needing review.
Instructions
列出历史模拟面试会话(含进度与状态)。
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
mock_interview_listList past mock interview sessions with progress and status so you can track practice history and identify areas needing review.
列出历史模拟面试会话(含进度与状态)。
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that each entry includes progress and status, but says nothing about ordering, pagination, scope (are sessions filtered to the current user?), or whether it is a safe read-only operation. That is a meaningful gap for a tool with zero annotation coverage.
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 front-loaded sentence with no filler; the verb and resource lead immediately. It is efficient, though arguably too terse to carry the return-value information the missing output schema would otherwise provide.
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?
Complexity is low (no params, no nesting), and the description partially covers return content by naming progress and status. However, with no output schema and no annotations, it omits ordering, pagination, and scope, which an agent would need to interpret the result set correctly.
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 zero parameters and schema coverage is 100%, so there is nothing for the description to document. Baseline 4 applies since parameter semantics are trivially satisfied.
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 (列出) and resource (历史模拟面试会话) plus the contents it surfaces (进度与状态). This clearly separates it from the action siblings (mock_interview_start / answer / end) and is unambiguous, though it does not explicitly name a contrasting alternative.
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 gives no when-to-use guidance, no prerequisites, and no mention of alternatives. It never explains how this differs from interview_review or when a listing is preferred over fetching a single review, leaving the agent to infer usage entirely.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.