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gowing111

@interviewsage/mcp

by gowing111

interview_coach

Score your answer to an interview question and receive actionable feedback: strengths, improvements, and a reference answer. Optionally include your resume for personalized coaching.

Instructions

单面陪练点评(会员)。对某道面试题的回答打分,并给出亮点、改进点与参考回答。需会员。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionYes面试题
resumeTextNo简历全文(可选,用于个性化点评)
userAnswerYes你的回答

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the transparency burden. It discloses membership requirements, the core scoring behavior, and the return content (score, highlights, improvement suggestions, reference answer). It could add more context about how the evaluation is generated, but the essential behavior is clear.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One compact sentence plus a membership note. Every phrase carries information: function, target input, output categories, and access level. The only slight redundancy is '(会员)' and '需会员', but it is minor and reinforces an important constraint.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a low-complexity tool with fully documented parameters and no output schema, the description provides enough operational context: required/optional inputs, membership, and expected output types. It lacks explicit routing guidance against sibling tools and a precise output structure, but those are modest gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

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 question, userAnswer, and optional resumeText. The main description adds no parameter-level detail beyond the schema, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific action ('对某道面试题的回答打分') and a concrete resource ('某道面试题的回答'). It also enumerates outputs (亮点、改进点、参考回答), making it easy to distinguish from siblings like interview_questions_bank (generates questions) and resume_tailor/rewrite (work on resumes).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly implies the use case: evaluate a user's answer to an interview question and provide feedback. It also states an access condition ('需会员'), which is a useful exclusion for non-members. It does not explicitly name alternatives or when-not-to-use conditions, so it stops short of a 5.

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

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