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io.github.neogeweb3/code-health-suite

io.github.neogeweb3/code-health-suite

by neogeweb3
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

analyze_change_impact

Assess the ripple effect of file changes: see direct and transitive dependents, affected tests, and an impact score. Use before refactoring to understand the blast radius.

Instructions

Analyze the ripple effect of changing specific files. Shows direct dependents, transitive impact, affected tests, and an impact score (fraction of project affected). Use before refactoring to understand blast radius.

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": {
      "path": "<path>",
      "changed_files": "<changed_files>"
    },
    "name": "analyze_change_impact"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYesProject root directory.
max_depthNoMax transitive dependency depth (default: 10).
changed_filesYesList of file paths (relative to root) that are being changed.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.8.1

TDQS

A4.4/5.0
Behavior4/5

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

The description discloses the tool's behavior by listing the types of information it returns (direct dependents, transitive impact, affected tests, impact score) and the metric (fraction of project affected). While there are no annotations, this explicit disclosure covers the main behavioral aspects, though it omits details like output format or error handling.

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 concise, using only two sentences to convey the purpose, outputs, and usage. No redundant information is present, and every sentence adds value.

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 provides a complete overview of what the tool does and the key outputs, which suffices for the given context. It does not formally document the output schema, but the description implies the return structure (direct dependents, transitive impact, etc.). This is adequate for a tool with no output schema defined.

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?

Each parameter has a description: path (project root), max_depth (max transitive dependency depth), and changed_files (list of files relative to root). The descriptions are clear and cover the purpose, but they do not elaborate on constraints like file format or required syntax, which is minor given the simplicity.

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: analyzing the ripple effect of changing files. It specifies the resource (files) and the action (analyze change impact), distinguishing it from sibling tools that focus on other metrics like complexity or dead code.

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 provides a clear usage context ('Use before refactoring to understand blast radius') and hints at the output (direct dependents, transitive impact, affected tests, impact score). However, it does not explicitly mention when not to use this tool versus alternatives, but the context is sufficient for typical scenarios.

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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