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Run project job

gitlab_run_project_job

Triggers a specific CI/CD job in a GitLab project using project_id and job_id.

Instructions

Run a specific job within a project.

Args: **kwargs: Additional parameters for the request (e.g., project_id, job_id).

Returns: Response: A wrapper containing the original response and a Job model.

Raises: MissingParameterError: If the project_id or job_id is missing. ParameterError: If invalid parameters are provided.

Input Schema

NameRequiredDescriptionDefault
pageNo
scopeNo
job_idNo
per_pageNo
max_pagesNo
project_idNo
pipeline_idNo
total_pagesNo
api_parametersNo
include_retriedNo
job_variable_attributesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv27.3.13

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare this is a non-readonly, open-world, non-idempotent mutation that is not destructive. The description adds useful error behavior (MissingParameterError, ParameterError) and return shape (wrapper with Job model), but does not explain side effects such as whether this triggers a manual job or how permission requirements apply.

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 first sentence is front-loaded and clearly states the action. The remaining Args/Returns/Raises block is somewhat boilerplate and generic, especially the **kwargs explanation, but it stays compact and readable.

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

Completeness2/5

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

For an 11-parameter mutation tool with no output schema and no parameter descriptions in the schema, the description is too thin. It names only two example parameters and omits most inputs, permission requirements, and side effects, so an agent cannot reliably infer how to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across 11 parameters, so the description carries the full burden. It only mentions project_id and job_id as examples inside **kwargs and does not explain pagination parameters, scope, pipeline_id, include_retried, job_variable_attributes, or api_parameters.

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 description states a specific verb and resource: run a specific job within a project. It is clear what the tool does, but it does not distinguish the action from closely related siblings such as gitlab_retry_project_job, gitlab_cancel_project_job, or gitlab_get_project_job.

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

Usage Guidelines2/5

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

The description gives no guidance on when to use this tool versus retrying, cancelling, or fetching a job. It only lists parameter examples and error conditions, leaving the agent to infer usage context from the tool name alone.

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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