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gitlab_trigger_pipeline

Trigger a CI pipeline on any branch or tag in a GitLab project, optionally passing custom CI variables.

Instructions

Trigger a new CI pipeline on the given branch or tag.

Args: ref: Branch name, tag, or SHA to run the pipeline on. project_path: GitLab project path, e.g. 'group/project'. variables: Optional dict of CI variable key/value pairs to inject.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refYes
variablesNo
project_pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description must fully disclose behavioral traits. It only states the action without detailing side effects (e.g., resource consumption, job execution), authentication needs, or potential errors. This is insufficient for an agent to understand the full implications of triggering a pipeline.

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 appropriately sized with a clear first sentence and a structured list of arguments. It avoids redundancy but could be slightly more succinct. Overall, it is well-organized and easy to parse.

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 covers the core parameters but lacks context about the output (though an output schema exists), asynchronous behavior, or any constraints. For a trigger action, more details on the resulting pipeline state would be helpful. It is adequate for basic use but not fully comprehensive.

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?

Schema description coverage is 0%, so the description must compensate. It provides clear semantic meaning for all three parameters: ref (branch/tag/SHA), project_path (with example), and variables (optional dict). This adds value beyond the bare schema types and names.

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 triggers a new CI pipeline on a specific branch or tag. This distinct verb+resource combination differentiates it from sibling tools like gitlab_get_pipeline (read-only) or gitlab_retry_pipeline (re-triggering an existing pipeline).

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

Usage Guidelines3/5

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

The description implicitly conveys when to use the tool (to start a new pipeline), but it provides no explicit guidance on when not to use it or which alternative tool to consider. For instance, it doesn't mention gitlab_retry_pipeline for retries or gitlab_get_pipeline for status checks.

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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