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CI/CD Pipeline Failure Detective
by Shandra
Diagnose CI/CD failures, isolate root causes from log noise, and generate precise remediation plans.
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See it in action
You say
Analyze these GitHub Actions logs from run #452. The build fails during the 'npm install' step but works fine on my local machine. Recent commits include a dependency update.
Your agent does
The first causal error is a lock-file mismatch. Your local environment uses npm v9, but the CI runner is pinned to v8, which ignores the new lock-file versioning. Remediation: Pin the CI runner to node v18.17+ to ensure npm v9 compatibility. Verification: Run 'npm ci' in the CI environment.
What you get
About this skill
The problem
CI/CD failures are noisy and deceptive. The last error in the log is rarely the root cause, and developers often waste hours retrying builds or chasing downstream symptoms instead of identifying the actual change that broke the pipeline.
What it does
- Analyzes build, test, and deployment logs to isolate the first causal error from secondary noise.
- Correlates recent commits, dependency lock-file changes, and infrastructure diffs with pipeline failures.
- Ranks root-cause hypotheses with confidence scores based on evidence rather than guesswork.
- Generates precise remediation steps, verification commands, and rollback guidance.
- Identifies flaky tests and environment drift between successful and failing runs.
Frameworks & tools
GitHub Actions, GitLab CI/CD, Jenkins, CircleCI, Azure Pipelines, Kubernetes, Docker, Terraform, Helm, and common package managers like npm, pip, and maven.
Why this beats prompting it yourself
Generic prompts often hallucinate fixes or recommend disabling quality gates just to get a green build. This skill follows a disciplined diagnostic workflow that enforces security boundaries, masks secrets, and requires evidence before claiming a cause is confirmed.
Use cases
- Debugging intermittent integration test failures caused by race conditions.
- Resolving deployment rollout failures in Kubernetes due to readiness probe mismatches.
- Identifying why a build fails in CI but passes on a local developer machine.
- Creating structured incident reports and remediation plans for engineering leads.
Known limitations
Cannot independently verify cloud provider status or rotate secrets without system access. Business-critical outages and destructive data operations require human oversight.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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Creator
Shandra is a top-ranked AI prompt creator and premium agent skill builder with an established track record in the AI marketplace. She is recognized as a #1 Top Seller on PromptBase, where she has built a trusted catalog of specialized AI prompts and agent skills for creators, entrepreneurs, educators, marketers, digital product sellers, and business professionals. With over 3,500 AI products published, more than 3,400 sales, and 1,000+ five-star reviews, Shandra has become known for creating practical, polished, and commercially useful AI resources that help users save time, organize complex ideas, generate high-quality content, build digital products, and transform creative concepts into actionable workflows. Her Agensi store focuses on premium, ready-to-use agent skills designed for real-world productivity. Each skill is developed with clear instructions, structured workflows, professional formatting, practical use cases, setup guidance, examples, edge-case handling, and a strong emphasis on usability. Her work combines creative strategy, prompt engineering, documentation design, business thinking, and practical automation into reliable tools that users can apply immediately. Shandra’s mission is to create AI skills that feel professional, useful, and complete from the first use — not generic templates, but carefully built workflow systems that help users think better, work faster, and produce stronger results.
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