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gitlab_pipeline_health

Read-onlyIdempotent

Analyze GitLab pipeline health by calculating success rates over 7 and 30 days with trend indicators for stand-ups and on-call handoffs.

Instructions

Aggregate success rate over 7 and 30 days with a trend indicator.

Great for stand-ups and on-call hand-offs. Returns success rate %, totals, last-10 statuses and a trend (up/down/flat).

Emits progress via the MCP Context (info log + report_progress) — useful in IDEs that show per-tool progress bars.

Examples: - "How stable is master" → default (ref='master', source='schedule') - "Push-driven pipeline health" → source='push' - Don't use for a single pipeline — use gitlab_get_pipeline.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refNoBranch to analyse.master
sourceNoPipeline source to include (typically 'schedule' or 'push').schedule
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
projectYes
refYes
sourceYes
rate_7dYes
rate_30dYes
trendYes
total_7dYes
success_7dYes
failed_7dYes
total_30dYes
success_30dYes
failed_30dYes
last_10_statusesYes
generated_atYes
Behavior4/5

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

The description adds valuable behavioral context beyond annotations: it explains the tool emits progress via MCP Context with info logs and report_progress, which is useful for IDEs with progress bars. This complements the readOnlyHint=true and destructiveHint=false annotations without contradicting them.

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?

The description is efficiently structured: it starts with the core functionality, then provides usage context, output details, behavioral notes, and specific examples. Every sentence adds value without redundancy, and the information is appropriately front-loaded.

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?

Given the tool has comprehensive annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint), 100% schema coverage, and an output schema exists, the description provides excellent context. It covers purpose, usage scenarios, behavioral traits, and sibling differentiation without needing to explain return values.

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?

With 100% schema description coverage, the schema already fully documents all three parameters. The description adds minimal param semantics through the examples showing typical use cases for 'ref' and 'source', but doesn't provide additional syntax or format details beyond what's in the schema.

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 aggregates success rates over 7 and 30 days with a trend indicator, specifying the exact metrics and timeframes. It distinguishes from sibling gitlab_get_pipeline by explicitly stating not to use it for single pipelines, making the scope and differentiation clear.

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?

The description provides explicit usage guidance: 'Great for stand-ups and on-call hand-offs' gives positive context, and 'Don't use for a single pipeline — use gitlab_get_pipeline' gives a clear alternative. The examples also show when to use different parameter combinations.

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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