mcp-lab-agent

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Ler estrutura do projeto

read_project

Reads package.json and test specifications from any framework (Cypress, Playwright, WDIO, Robot, pytest) to return project context. Optionally includes example code from test files.

Instructions

Lê package.json, specs existentes (qualquer framework: Cypress, Playwright, WDIO, Robot, pytest, etc) e retorna contexto. Use includeContent para trazer código de exemplos.

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": "read_project"
  }
}

Input Schema

Name	Required	Description	Default
`maxFiles`	No	Máximo de arquivos cujo conteúdo será lido. Default: 3.
`includeContent`	No	Se true, inclui conteúdo dos primeiros 3 arquivos de teste como referência. Default: false.

Output Schema

Name	Required	Description	Default
`ok`	Yes
`summary`	Yes
`testFiles`	No
`packageJson`	No
`testFilesWithContent`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.3.1Aug 2, 2026

TDQS

A3.8/5.0

Behavior3/5

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

No annotations are provided, so the description carries the burden of disclosing behavior. It clearly indicates a read-only operation by using 'Lê' and specifies the files it processes, but it leaves 'retorna contexto' vague without describing output structure or potential side effects like recursion limits. The read-only intent is clear, but additional behavioral details are missing.

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 two short, front-loaded sentences. The first states the core purpose, and the second gives a usage tip. Every word earns its place, with no extraneous information.

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 simple, and an output schema exists (though not shown) to explain return values. The description covers what files are read and the includeContent option, while the schema covers maxFiles. It could mention whether it scans recursively or ignores certain directories, but overall it is adequate for a read-only project inspection 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?

The input schema covers both parameters with descriptions, so the baseline is 3. The description adds minimal extra by explaining includeContent's purpose ('trazer código de exemplos'), but it does not elaborate on maxFiles beyond the schema default. The schema does the heavy lifting for parameter understanding.

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 reads package.json and existing specs for any test framework and returns context. The verb 'Lê' is specific and the resource is well-defined, distinguishing it from read_file which reads arbitrary files. The scope is explicit and unambiguous.

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 using this tool to gather project context and examples, and provides a tip on using includeContent for example code. However, it does not explicitly contrast with sibling tools like detect_project or read_file, nor does it specify when not to use it. Usage is implied rather than explicitly guided.

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