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Fetch, extract, and cross-reference a failed run in one call

triage_pipeline_failure

Diagnose failed CI pipeline runs by fetching logs, parsing failure signals, and finding similar past failures, providing all data needed to write an explanation in a single call.

Instructions

Convenience tool that chains fetch_pipeline_run -> (download every JUnit/Surefire-looking artifact for the run, and every failed job's log) -> extract_failure_signal's parsers -> find_similar_past_failures. Returns everything needed to write the explanation in one call. Use the granular tools instead when you want to target one specific job. The response includes a dashboardConfigured flag -- if true, ask the user whether they'd like this triage published before calling publish_triage; don't publish automatically.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoYesRepository name, e.g. "playwright-typescript-framework"
ownerYesRepository owner/org, e.g. "krishanchawla"
runIdNoSpecific run ID. Omit to use the latest failed run on `branch`.
branchNomain
Behavior4/5

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

With no annotations, the description carries the burden. It discloses the entire pipeline chain, including downloading artifacts/logs and running parsers/search, and mentions the dashboardConfigured flag behavior. It doesn't mention potential performance costs of downloading artifacts or any side effects, but overall it's quite transparent about how the tool behaves.

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 two dense sentences that front-load the purpose and chain, then add a usage alternative and a critical publishing caution. It is efficient but slightly long; every sentence earns its place.

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 complex chained tool with no output schema or annotations, the description covers the pipeline, what it returns at a high level, and a key behavioral caveat. It lacks a detailed return structure, but for the purpose of selecting and invoking the tool, it is sufficiently complete.

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 coverage is 75% (branch lacks a description), so baseline is 3. The description does not add parameter-level details beyond what the schema already provides, but the composite nature implies the parameters align with fetch_pipeline_run. No extra meaning is added.

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 this is a convenience tool that chains fetch_pipeline_run, artifact/log downloads, extract_failure_signal's parsers, and find_similar_past_failures, returning everything needed to write an explanation. It explicitly distinguishes itself from granular siblings by advising to use those when targeting a specific job.

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?

Explicitly states when to use (want a full triage in one call) and when not to (when targeting one specific job, use granular tools). Also provides a post-call guideline about asking the user before publishing if dashboardConfigured is true.

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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