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validate_ci_lint

Read-only

Validate GitLab CI/CD YAML content to catch configuration errors before applying changes. Read-only linting returns errors for invalid identifiers or permissions, letting you verify pipeline syntax safely.

Instructions

Validate provided GitLab CI/CD YAML content 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
refNoBranch or tag context for dry_run validation
contentYesGitLab CI/CD YAML content to validate
dry_runNoRun pipeline creation simulation
jmespathNoOptional JMESPath expression filtering the JSON result before return.
project_idYesProject ID or URL-encoded path
include_jobsNoInclude jobs in the lint response

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2.1.66
    • addedInput schema / properties / jmespath
      Added value: +{
+  "description": "Optional JMESPath expression filtering the JSON result before return.",
+  "type": "string"
+}
  2. Changed1 schema field changedv2.1.62
    • changedInput schema / required
      Previous value: -[
-  "content",
-  "project_id"
-]New value: +[
+  "project_id",
+  "content"
+]
  3. Addedv2.1.45
  4. Removedv2.1.43
  5. Addedv2.1.18
  6. Removedv2.1.14
  7. Addedv2.1.11
  8. Removedv2.1.10
  9. Addedv2.1.9

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, and the description reinforces this consistently. It adds genuine value beyond annotations by disclosing error behavior: 'missing resources, invalid identifiers, insufficient permission, and rate limits are returned as errors.' This is exactly the kind of failure-mode context an agent needs and that structured fields don't provide.

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?

Well-structured: purpose first, then usage guidance, then behavioral details. Three sentences carry real information with minimal waste. Small deductions for the redundant restatement of the read-only annotation and the stray `group_id` reference, but overall tight and front-loaded.

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?

With no output schema, the description bears the burden of explaining what the agent should expect back, yet it never describes the lint response format (valid/invalid indicators, errors, warnings, jobs). It also fails to differentiate from the near-twin sibling `validate_project_ci_lint`. Coverage of usage timing, safety, and error modes is solid, so the tool is usable, but these gaps keep it at adequate rather than complete.

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?

Schema description coverage is 100%, so the baseline is 3. The description adds little beyond the schema: the guidance to 'provide the numeric ID or complete URL-encoded path' merely restates the schema's own 'Project ID or URL-encoded path' description. The mention of `group_id` is actually confusing since no such parameter exists in the schema.

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 opening sentence states a specific verb and resource: 'Validate provided GitLab CI/CD YAML content for a project.' It also implicitly distinguishes itself from mutation tools via the 'without applying it' framing. However, sibling `validate_project_ci_lint` exists and the description never differentiates this tool from that near-twin, so an agent cannot tell which lint validator to pick.

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?

'Use this to check configuration without applying it; choose a create or update tool only after validation succeeds' provides explicit workflow sequencing and a clear when-to-use directive. It stops short of naming specific alternative tools or stating when NOT to use this tool in favor of `validate_project_ci_lint`, leaving that sibling distinction unaddressed.

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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