@interviewsage/mcp

resume_rewrite

Rewrite your resume using the STAR method to restructure experience and optimize wording. Get the complete revised resume with a detailed change summary for members.

Instructions

简历改写（会员）。用 STAR 法则重构经历、优化措辞，返回改写后的完整简历与改动说明。需会员。

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "resumeText": "<resumeText>"
    },
    "name": "resume_rewrite"
  }
}

Input Schema

Name	Required	Description	Default
`resumeText`	Yes	简历全文文本（纯文本）

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 6, 2026

TDQS

A3.8/5.0

Behavior4/5

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

With no annotations provided, the description carries the full behavioral burden. It discloses the transformation approach (STAR), the return format (full resume and change explanation), and the access requirement (membership). It could say more about side effects or failure behavior, but for a text-transform tool these key behaviors are covered.

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?

The description is two short sentences with no filler. It front-loads the core action, then adds method, output, and access requirements. Every clause earns its place.

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 single-parameter, stateless-seeming rewrite tool, the description is largely complete: it states inputs implied by schema, output structure, method, and membership restriction. It could be slightly more complete by naming when to use it instead of resume_tailor, but that gap is already reflected in the usage_guidelines score.

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 input parameter is already well documented as the full plain-text resume. The description does not add parameter-specific meaning beyond what the schema provides, which matches the baseline for high schema coverage.

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

Purpose4/5

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

The description clearly states the operation: rewriting a resume using the STAR method and refining wording. It also names the output (full rewritten resume plus change notes), which helps distinguish it from diagnostic or interview-related siblings, though it does not explicitly contrast with resume_tailor or resume_diagnose.

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

Usage Guidelines3/5

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

The intended use is implied: the agent should call this when the user requests a STAR-based resume rewrite. However, it does not explicitly say when to prefer this tool over resume_tailor or resume_diagnose, and it only offers a membership precondition rather than selection criteria.

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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