Skip to main content
Glama

Delimit Test Coverage

delimit_test_coverage
Read-onlyIdempotent

Analyze project test coverage against a threshold to provide a pass/fail signal for CI.

Instructions

Analyze test coverage for a project (experimental).

When to use: to surface coverage by file/folder against a threshold when you need a pass/fail signal for CI. When NOT to use: to scaffold new test stubs (use delimit_test_generate) or run a smoke run (delimit_test_smoke).

Sibling contrast: delimit_test_smoke validates that tests run at all; delimit_test_generate writes test scaffolds; this measures coverage of existing tests.

Side effects: read-only inspection. Calls backends.ui_bridge.test_coverage. Marked experimental — coverage runner detection is heuristic.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
thresholdNoCoverage percentage threshold for pass/fail. Default 80.
project_pathYesPath to the project root. Required.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changedv4.7.9
    • changedInput schema / properties / project_path / description
      Previous value: -"Project path."New value: +"Path to the project root. Required."
    • changedInput schema / properties / threshold / description
      Previous value: -"Coverage threshold percentage."New value: +"Coverage percentage threshold for pass/fail. Default 80."
  2. Addedv4.5.5

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnlyHint/idempotentHint/destructiveHint annotations, the description discloses additional behavioral details: 'Side effects: read-only inspection', the backend call 'backends.ui_bridge.test_coverage', and the experimental nature with 'coverage runner detection is heuristic'. This significantly exceeds the annotation baseline.

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 well-structured with clear labeled sections (When to use, When NOT to use, Sibling contrast, Side effects, calls, experimental note). Each sentence adds meaningful information, and the most important purpose statement is front-loaded in the first sentence.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers purpose, usage boundaries, side effects, backend integration, and experimental caveats. Since an output schema exists, no return value details are required. The context is sufficiently complete for an agent to decide when and how to use 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 input schema already provides complete descriptions for both parameters ('threshold' and 'project_path'), covering semantics and defaults. The tool description does not add any parameter-specific detail beyond what the schema states, so it stays at the baseline for high schema coverage.

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 function: 'Analyze test coverage for a project' and explains it surfaces coverage by file/folder against a threshold. It explicitly distinguishes itself from sibling tools delimit_test_smoke and delimit_test_generate, making its unique purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit 'When to use' (CI pass/fail on coverage thresholds) and 'When NOT to use' sections, naming specific alternative tools for other use cases. The sibling contrast paragraph reinforces when to choose this tool over delimit_test_smoke and delimit_test_generate.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/delimit-ai/delimit-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server