Skip to main content
Glama
Sign In
io.github.neogeweb3/code-health-suite

io.github.neogeweb3/code-health-suite

by neogeweb3
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

analyze_type_coverage

Analyze Python type annotation coverage: function signatures, parameters, return types, Any usage, type: ignore comments. Returns per-file metrics and coverage percentages to pinpoint untyped code.

Instructions

Analyze Python type annotation coverage: function signatures, parameters, return types, Any usage, and type: ignore comments. Returns per-file metrics and coverage percentages.

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>"
    },
    "name": "analyze_type_coverage"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYesFile or directory path to analyze.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.8.1

TDQS

A3.5/5.0
Behavior3/5

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

It discloses the output (per-file metrics and coverage percentages) but does not mention side effects, limitations, or potential performance implications, though as a read-only analysis tool, this is acceptable.

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 efficiently conveys the tool's purpose without unnecessary detail.

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?

It explains the return value, but lacks details on recursion behavior, error handling, or prerequisites, though the basic output is covered.

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 single parameter 'path' is clearly described in the schema as a file or directory path, and the description reinforces this by mentioning per-file metrics, so no additional detail is needed.

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 analyzes Python type annotation coverage and lists specific aspects (function signatures, parameters, return types, Any usage, type: ignore comments), distinguishing it from other analysis tools.

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 does not mention when to use this tool over other analysis tools, lacking guidance on appropriate scenarios or alternatives.

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

Deploy Server

Other Tools