GPA Backend Test Analyst MCP

reverse_engineer_module

Analyzes undocumented code to produce functional descriptions, input/output contracts, dependencies, and risk assessments for backend modules.

Instructions

Analisa código sem documentação e gera: descrição funcional, contratos de entrada/saída, dependências e riscos.

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": {
      "code_snippet": "<code_snippet>",
      "language": "<language>"
    },
    "name": "reverse_engineer_module"
  }
}

Input Schema

Name	Required	Description
`code_snippet`	Yes	Trecho de código a ser analisado
`language`	Yes	Linguagem de programação do código
`context`	No	Contexto do módulo (ex: 'checkout service', 'order management')

Schema Changelog

Changes observed during successful MCP inspections.

First observedv4.0.0Jun 24, 2026

TDQS

B3.1/5.0

Behavior2/5

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

No annotations provided, so description should fully cover behavioral traits. It mentions outputs but not side effects, permissions, rate limits, or whether the tool is read-only. This is minimal disclosure for a reverse engineering tool.

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

Conciseness4/5

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

Description is a single concise sentence with no fluff. It could be more structured (e.g., bullet points) but remains efficient.

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

Completeness2/5

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

Lacks completeness: no output schema, no information on return format, code size limits, or language-specific nuances. For a complex analysis tool, more context is needed.

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%, and descriptions are clear. The tool description adds no extra parameter meaning beyond what's already in the schema, so baseline 3 is appropriate.

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?

Description clearly states the tool analyzes undocumented code and generates specific outputs (functional description, contracts, dependencies, risks). The verb 'analisa' and resource 'código' are specific, and it distinguishes from siblings like 'analyze' which is generic.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives like 'task_reverse_engineer' or 'analyze'. The description implies usage for undocumented code but lacks explicit context or exclusions.

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