mcp-lab-agent

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Comparar com padrões da indústria

qa_compare_with_industry

Compare your project's QA metrics like coverage, success rate, and execution time against industry benchmarks to identify performance gaps.

Instructions

[BENCHMARK] Compara as métricas do seu projeto com benchmarks da indústria (cobertura, taxa de sucesso, tempo de execução).

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": "qa_compare_with_industry"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
`verdict`	Yes
`industry`	Yes
`yourProject`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.3.1Aug 2, 2026

TDQS

A3.7/5.0

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 of behavioral disclosure. It states the core action (comparing metrics) but does not explicitly disclose whether it is read-only, how benchmarks are obtained, or any limitations. The non-destructive nature is implied but not stated.

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, well-structured sentence that front-loads the purpose with a helpful [BENCHMARK] tag. It includes the types of metrics compared (coverage, success rate, execution time) without any fluff 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?

The description adequately covers the tool's purpose and comparison criteria. Since an output schema exists, return values do not need to be detailed. The tool is simple (no parameters), and the description provides sufficient context for selection and invocation, though it could mention prerequisites like having test metrics available.

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 the schema trivially covers 100% of the inputs. The description appropriately does not discuss parameters, which is correct given the 0-param count. The baseline for no parameters is 4, and nothing lowers it.

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 states the tool compares project metrics against industry benchmarks, specifying coverage, success rate, and execution time. It uses a specific verb and resource, but does not explicitly differentiate from sibling tools beyond the [BENCHMARK] tag.

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 the tool is used for benchmarking project metrics against industry standards, but it does not provide explicit guidance on when to use it versus alternatives or when not to use it. The context is clear enough, but no exclusions or alternative recommendations are given.

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