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validate_project_ci_lint

Read-only

Check a project's GitLab CI configuration for errors before applying it. This read-only lint validates .gitlab-ci.yml content and reports invalid identifiers or missing resources.

Instructions

Validate an existing .gitlab-ci.yml configuration for a project. Use this to check configuration without applying it; choose a create or update tool only after validation succeeds. It is read-only and does not mutate GitLab data; missing resources, invalid identifiers, insufficient permission, and rate limits are returned as errors. When project_id or group_id is accepted, provide the numeric ID or complete URL-encoded path described by the schema; use required identifiers and pagination fields exactly as documented.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dry_runNoRun pipeline creation simulation
project_idYesProject ID or URL-encoded path
content_refNoCommit SHA, branch, or tag to read the existing CI config from
dry_run_refNoBranch or tag context for dry_run validation
include_jobsNoInclude jobs in the lint response

Schema Changelog

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

  1. Addedv2.1.45
  2. Removedv2.1.43
  3. Addedv2.1.18
  4. Removedv2.1.14
  5. Addedv2.1.11
  6. Removedv2.1.10
  7. Addedv2.1.9

TDQS

A4.2/5.0
Behavior4/5

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

The description explicitly states 'It is read-only and does not mutate GitLab data', aligning with the readOnlyHint annotation. It additionally mentions error conditions: 'missing resources, invalid identifiers, insufficient permission, and rate limits are returned as errors.' This goes beyond the annotation but does not describe the success response format, which would be expected without an output schema.

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 somewhat verbose, containing multiple sentences with some redundancy (e.g., 'read-only' and 'does not mutate' are repeated). However, it is still concise enough and well-structured, covering purpose, usage, and error behavior in a logical order. It could be tightened but is not excessively long.

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?

The description lacks information about the success response format. Since there is no output schema, the user is left unaware of what the tool returns on a successful validation. It mentions error cases but not the successful result structure. This is a clear gap, especially for a tool that is intended to be used before mutations. It could be improved by specifying the response contains validation status and any errors.

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?

The schema provides 100% description coverage for all parameters. The description adds a note: 'When `project_id` or `group_id` is accepted, provide the numeric ID or complete URL-encoded path described by the schema', which gives formatting guidance. However, it references 'group_id' which is not in the schema, creating a minor inconsistency. Overall, the parameter meaning is well covered by the schema plus the added context.

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: 'Validate an existing .gitlab-ci.yml configuration for a project.' It also distinguishes it from mutation tools by stating 'Use this to check configuration without applying it; choose a create or update tool only after validation succeeds.' This is specific 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 Guidelines4/5

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

The description explicitly tells when to use the tool: 'Use this to check configuration without applying it; choose a create or update tool only after validation succeeds.' It also notes that it is read-only, implying safe use. However, it does not contrast with the sibling tool 'validate_ci_lint', which might be a project-agnostic variant. Nevertheless, the provided guidance is clear for the primary use case.

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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