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mcp-gitlab-crunchtools

mcp-gitlab-crunchtools

by crunchtools
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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List Pipeline Jobs Tool

list_pipeline_jobs_tool
Read-only

Retrieve jobs for a GitLab CI/CD pipeline by project and pipeline ID, with optional scope filtering and pagination to inspect job statuses and results.

Instructions

List jobs for a CI/CD pipeline.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "project_id": "<project_id>",
      "pipeline_id": "<pipeline_id>"
    },
    "name": "list_pipeline_jobs_tool"
  }
}

Input Schema

NameRequiredDescriptionDefault
pageNoPage number (default: 1)
scopeNoFilter by job scope (created, pending, running, failed, success, canceled, skipped, manual)
per_pageNoResults per page, max 100 (default: 20)
project_idYesProject ID or path
pipeline_idYesPipeline ID

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.6.0
    • addedInput schema / properties / pipeline_id / minimum
      Added value: +1
  2. First observedv0.4.1

TDQS

C2.9/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. However, the description adds nothing beyond the annotation - no mention of pagination behavior, filters, or ordering - which for a list tool with page/per_page parameters would be genuinely useful context.

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?

A single short sentence, front-loaded with the action and resource. It is efficient, though the terseness borders on under-specification rather than ideal conciseness.

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 an output schema, complete parameter documentation, and a read-only annotation, the structured data carries most of the burden. The description is still incomplete on usage context and pagination/filtering behavior, which an agent would want for a 5-parameter list tool.

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 all five parameters, including the scope enum values and per_page cap, are already documented in the schema. The description adds no parameter meaning beyond that baseline.

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?

States a specific verb (List) and resource (jobs for a CI/CD pipeline), which is unambiguous. It does not differentiate from siblings such as get_job_log_tool or list_pipelines_tool, leaving the agent to infer the boundary between listing jobs and listing pipelines.

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 when-to-use guidance, no prerequisites, and no reference to alternatives like list_pipelines_tool or get_job_log_tool. The agent must derive usage purely from the name and schema.

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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