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Claude Code Starter Kit MCP

Claude Code Starter Kit MCP

by dachivadachkoria
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

command_test_coverage

Analyze test coverage to identify uncovered code and automatically generate tests for those areas.

Instructions

Analyze test coverage and generate tests for uncovered code

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": "command_test_coverage"
  }
}

Input Schema

NameRequiredDescriptionDefault
argumentsNoOptional arguments for the tool (e.g. a file path or flags like --changed, --dry-run).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are present, so the description must fully disclose behavior. While it states the tool analyzes coverage and generates tests, it omits important traits such as whether it modifies files, runs tests, requires permissions, or has side effects. This is a significant gap for a generative 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?

The description is a single, concise sentence that front-loads the core purpose. It is appropriately short for a low-complexity tool, though it could include slightly more detail without losing conciseness.

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?

Given the low complexity (one optional parameter, no output schema), the description is minimally viable but incomplete. It lacks details on input format, expected output, and behavioral constraints, leaving the agent uncertain about how to invoke the tool correctly.

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 has 100% description coverage for its single parameter, and the parameter description provides examples (file path, --changed, --dry-run). However, the tool description adds only marginal value beyond the schema, as the examples are generic and do not explain how to use them effectively or what each flag does.

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 tool's purpose: analyzing test coverage and generating tests for uncovered code. It uses a specific verb ('analyze', 'generate') and resource ('test coverage'). However, it does not explicitly distinguish itself from similar siblings like command_test or agent_test_engineer, which could also handle coverage tasks.

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?

The description provides no guidance on when to use this tool versus alternatives (e.g., command_test or agent_test_engineer). There are no exclusions, prerequisites, or context provided. Usage is only implied by the tool's name.

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

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