mcp-lab-agent

by Wesley-Gomes93

Overview Schema Source Related Servers Discussions Admin

JavaScript

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Sugerir correção para falhas

suggest_fix

Suggests code fixes (patch, refactor) based on failure analysis, addressing test failures with actionable solutions.

Instructions

Recebe análise de falhas e sugere correções (patch, refactor, etc.).

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": {
      "failures": "<failures>"
    },
    "name": "suggest_fix"
  }
}

Input Schema

Name	Required	Description	Default
`failures`	Yes	Resultado de analyze_failures.

Output Schema

Name	Required	Description	Default
`ok`	Yes
`suggestions`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.3.1Aug 2, 2026

TDQS

B3.3/5.0

Behavior2/5

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

With no annotations available, the description must bear the full burden of disclosing behavioral traits. It only states that it 'suggests fixes' without clarifying whether the tool modifies files, requires special permissions, or returns a structured patch. The ambiguous 'etc.' adds further vagueness, leaving side effects and output behavior undisclosed.

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, front-loaded sentence with no redundant words. The 'etc.' is slightly vague but does not add bloat. It is appropriately concise for the tool's simple purpose.

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

Completeness3/5

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

While the tool is simple (one parameter, output schema exists), the description lacks workflow context such as the expected input source (analyze_failures) or any constraints on use. It is adequate but leaves clear gaps in how and when the tool fits into a larger QA pipeline.

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?

The schema already provides 100% coverage for the single 'failures' parameter, describing it as 'Resultado de analyze_failures.' The description does not add any parameter-specific semantics, so it stays at the baseline level without exceeding the schema's detail.

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 identifies the action ('sugere correções' – suggests fixes) and the resource (failure analysis), making the purpose evident. However, it does not differentiate itself from the sibling tool 'suggest_selector_fix' or other fix-related tools, earning a 4 rather than 5.

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 description implies that this tool should be used after analyzing failures, but it does not explicitly state when to use it over alternatives. No exclusions or comparisons are provided, so the guidance remains implicit rather than explicit.

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