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gitlab_trigger_pipeline

Trigger a new GitLab CI pipeline on a specified branch or tag with optional CI variables. Each call creates a new pipeline and consumes runner minutes.

Instructions

Create a new pipeline on the given ref, optionally with CI variables.

Not idempotent: each call creates a new pipeline. Consumes minutes on your runners — avoid calling in loops.

Examples: - "Run the pipeline on master" → default (ref='master') - "Run the pipeline on feature/x with DEBUG=1" → ref='feature/x', variables={'DEBUG': '1'} - Don't call to retry — use gitlab_retry_pipeline which keeps the same pipeline ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refNoBranch or tag to run the pipeline on.master
variablesNoOptional CI variables to pass to the pipeline (``{key: value}``).
project_pathNoGitLab project path (e.g. 'my-org/my-repo'). When omitted, the default from GITLAB_PROJECT_PATH env var is used.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
pipeline_idNo
statusNo
web_urlNo
refNo
created_atNo
status_noteNo
Behavior4/5

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

Description adds context beyond annotations: not idempotent (matches hint), consumes runner minutes, and advises against loops. No contradiction with annotations (readOnlyHint=false, destructiveHint=false, idempotentHint=false).

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?

Extremely concise: one sentence for purpose, one for behavioral warning, and bulleted examples. No wasted words.

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?

With output schema present and good annotations, description is complete. Covers purpose, behavior, cost implications, and alternatives. Examples cover typical usage patterns.

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 covers all parameters with descriptions (100% coverage). Description provides examples but does not add significant new semantic meaning beyond what schema provides. Baseline 3 is appropriate.

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?

Clearly states 'Create a new pipeline on the given ref' with specific verb and resource. Distinguishes from sibling 'gitlab_retry_pipeline' by noting it creates a new pipeline vs. retrying.

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?

Explicitly warns of non-idempotency, runner minutes consumption, and loops. Directs to 'gitlab_retry_pipeline' for retries. Provides concrete examples for common use cases.

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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