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CodeGuard

by Skhaaall
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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schema_check

Detect missing fields and desynchronized enums between Prisma schema, backend DTOs, and frontend types. Run after schema or DTO changes to maintain coherence.

Instructions

Coherence Prisma ↔ DTOs backend ↔ types frontend. Detecte les champs manquants et les enums desynchronises. A lancer apres modification du schema Prisma ou des DTOs.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "schema_check"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.2

TDQS

A4.4/5.0
Behavior4/5

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

There are no annotations, so the description carries the behavioral burden. It discloses that the tool detects coherence issues rather than mutating anything, and it scopes the behavior to missing fields and enum drift. It does not mention output or side effects, but for a detection tool this is adequate.

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?

Three short sentences: scope, specific checks, and run trigger. Every sentence earns its place and the key purpose is front-loaded. No filler or repetition.

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 zero-parameter check tool with no output schema, the description provides enough context: what is checked, what kinds of problems are found, and when to run it. It could mention how results are reported, but that is not essential given the simplicity of the tool.

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

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so there is nothing for the description to document beyond the fact that it needs none. The context about when to run it adds practical meaning even though no parameter details are required.

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 names a specific resource (Prisma schema, backend DTOs, frontend types) and a specific action: detecting missing fields and desynchronized enums. This clearly distinguishes schema_check from generic siblings like status or check.

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 explicitly states when to run the tool: after modifying the Prisma schema or DTOs. It does not list alternatives or when-not-to-use, but the trigger context is clear enough for an agent to select it appropriately.

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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