mcp-lab-agent

Overview Schema Source Related Servers Discussions Admin

Modo autônomo: gera, roda, corrige e aprende

qa_auto

Autonomously generates and runs tests, analyzes failures, applies fixes, and iterates until tests pass or retry limit is reached.

Instructions

[AGENTE AUTÔNOMO] Loop completo: detecta projeto → gera teste → roda → se falhar: analisa, corrige, roda de novo → aprende com erros. Repete até passar ou atingir max_retries.

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": {
      "request": "<request>"
    },
    "name": "qa_auto"
  }
}

Input Schema

Name	Required	Description
`request`	Yes	O que testar (ex: 'login flow', 'checkout', 'API /users').
`framework`	No	Framework (detectado automaticamente se omitido).
`maxRetries`	No	Máximo de tentativas de correção. Default: 3.

Output Schema

Name	Required	Description	Default
`ok`	Yes
`error`	No
`attempts`	Yes
`learnings`	No
`finalStatus`	Yes
`testFilePath`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.3.1Aug 2, 2026

TDQS

A4/5.0

Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses the loop behavior, retry logic, and learning from errors. However, it doesn't explicitly warn about side effects like modifying files or potentially long execution times, which could be important for an agent to consider.

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 a single sentence that effectively uses arrows to outline the sequential loop. It is dense but efficient, with no wasted words, and clearly front-loads the autonomous agent concept.

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 is complex, but the description covers the essential workflow steps and the stopping condition. An output schema exists, so return values need not be explained. It doesn't mention prerequisites or edge cases (e.g., no project detected), but the description is sufficiently complete for an agent to invoke the tool.

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 baseline is 3. The description mentions max_retries and auto-detection of framework, but these add no new meaning beyond what the schema already provides. The 'request' parameter is not elaborated further.

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 clearly states the tool's purpose: an autonomous agent that generates, runs, fixes, and learns from tests in a loop. This distinctively differentiates it from siblings like generate_tests or run_tests, which each handle a single step.

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 when to use this tool (for a complete autonomous loop) versus manually calling steps like generate_tests, run_tests, and analyze_failures. However, it doesn't explicitly name alternatives or state exclusions, so it falls 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.