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Get pipeline test report summary

get_pipeline_test_report_summary
Read-onlyIdempotent

Get aggregate test-report counts and pass/fail/error totals for a GitLab pipeline. Provide project and pipeline ID.

Instructions

Get aggregate test-report counts and pass/fail/error totals for one pipeline.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectYesGitLab project ID or full path such as group/project.
pipeline_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYesGitLab response normalized for model use.
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is well covered. The description's contribution—that output consists of pass/fail/error totals—is useful but does not add deep behavioral context beyond what annotations and the name imply. No contradiction between description and annotations.

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?

A single, front-loaded sentence with zero filler. Every word earns its place: 'Get' states the action, 'aggregate test-report counts and pass/fail/error totals' specifies the output, and 'for one pipeline' sets the scope.

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

Completeness4/5

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

For a low-complexity read tool with only 2 parameters, rich annotations, and an output schema (which handles return-value documentation), the description is complete. It doesn't discuss edge cases like empty test reports, but the presence of an output schema and openWorldHint mitigates this gap.

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 50%: 'project' is well-described in the schema, while 'pipeline_id' lacks an inline description. The description adds no parameter-specific semantics, but both parameter names are self-explanatory and the schema handles the harder case (project ID or full path). The description neither compensates nor detracts—adequate baseline.

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 uses a specific verb ('Get') plus precise resource details ('aggregate test-report counts and pass/fail/error totals') and scope qualifier ('for one pipeline'). This clearly differentiates it from the sibling get_pipeline_test_report (full report) by emphasizing the aggregated/summary nature of the output.

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?

The description provides clear context: it returns aggregate counts for exactly one pipeline, which implies when to choose it (summary needs) vs. alternatives like get_pipeline_test_report (raw data) or list_pipelines (pipeline listing). It stops short of naming alternatives explicitly, hence not a 5.

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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