MCP Tool Auditor

rewrite_tool_description

Rewrites weak tool descriptions into clear, LLM-optimized versions with usage guidelines, parameter hints, and limitations. Produces an improved description ready to paste into your MCP server.

Instructions

Rewrite a weak tool description into a high-quality, LLM-optimized version that follows current best practices (clear purpose, usage guidelines, parameter hints, limitations). Returns the improved description ready to paste into your MCP server.

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": {
      "name": "<name>",
      "description": "<description>"
    },
    "name": "rewrite_tool_description"
  }
}

Input Schema

Name	Required	Description
`name`	Yes	Tool name
`context`	No	Optional extra context about when the tool should be used
`description`	Yes	Current (weak) description
`inputSchema`	No	JSON Schema of parameters (helps generate better parameter guidance)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Aug 10, 2026

TDQS

A4/5.0

Behavior3/5

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

No annotations are provided, so the description carries the transparency burden. It discloses the output ('Returns the improved description ready to paste into your MCP server') but doesn't disclose any limitations or side effects, though it's likely a pure text transformation.

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 sentences, front-loads the main purpose, and includes no unnecessary information.

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?

The tool has a simple purpose, 4 parameters with full schema coverage, and the description explains the return value. It could benefit from explicit usage guidance relative to sibling tools, but it is otherwise adequate.

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 coverage is 100%, so each parameter has a description. The tool description mentions best practices that incorporate parameter hints, but doesn't add specific parameter semantics beyond the schema.

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?

The description explicitly states 'Rewrite a weak tool description into a high-quality, LLM-optimized version', which clearly identifies the action and resource. It also distinguishes itself from sibling tools by focusing on rewriting rather than auditing or fetching best practices.

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 implies use when a tool description is weak and needs improvement, by saying 'Rewrite a weak tool description'. It doesn't explicitly mention alternative tools or exclusions, but the context is clear enough.

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

Deploy Server