Investigates a specific CI failure to a verdict: whose fault, which commit, who wrote it, and whether it's fixed. Use for "who broke master", "why did this test fail in CI", "is this failure my PR's fault or everyone's", "is this test flaky or actually broken", "when did this failure start". Works from the engineering_analytics warehouse views (engineering_analytics_ci_failures, engineering_analytics_ci_job_history) plus the CI failure logs. Not for aggregate CI health, cost, or merge bottlenecks (use diagnosing-ci-and-merge-bottlenecks) and not for building saved insights (use turning-engineering-analytics-into-insights).
80
100%
Does it follow best practices?
Run evals on this skill
Adds up to 20 points to the overall score
View guide
Low
Low-risk findings worth noting
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
The workflow executes SQL queries that read failure/test strings and commit metadata from outsider-origin CI logs/warehouse tables (e.g., `engineering_analytics_ci_failures.test_id` / `error_signature` and `engineering_analytics_ci_job_history.commit_message`), so those outsider-authored free-text fields can be returned by `execute-sql` and thereby enter the agent’s LLM context.
6ba1e0a
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.