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    workflow-speed-optimizer

    by Markus Isaksson

    Audit and refactor CI/CD pipelines to slash build times and cloud costs using platform-native optimizations.

    Updated May 2026
    Security scanned
    One-time purchase

    $9

    One-time purchase

    ⚡ Also available via Agensi MCP — your AI agent can load this skill on demand via MCP. Learn more →

    Included in download

    • Implement lockfile-keyed caching for faster dependency installation
    • Parallelize slow test suites using matrix strategies and sharding
    • terminal automation included
    • Includes example output and usage patterns
    • Instant install

    See it in action

    Findings:
    1. Caching: missing npm cache (Saves ~90s)
    2. Triggers: doc changes trigger tests (Saves 100% on doc PRs)
    
    Optimized YAML:
    test:
      runs-on: ubuntu-latest
      steps:
        - uses: actions/setup-node@v4
          with:
            cache: 'npm'
        - run: npm ci
        - name: coverage
          retention-days: 7

    About This Skill

    Performance-First CI/CD Auditing

    CI/CD pipelines are often the biggest bottleneck in a developer's fast inner loop and a major source of hidden cloud costs. The Workflow Speed Optimizer is a specialized skill designed to audit and refactor existing GitHub Actions, GitLab CI, and CircleCI configurations to maximize efficiency.

    What it does

    This skill goes beyond simple linting by performing a deep structural audit of your YAML configurations across four critical categories:

    • Dependency Caching: Implementing lockfile-keyed caching for npm, pip, cargo, maven, and more to skip redundant installs.
    • Intelligent Parallelization: Implementing matrix strategies and test sharding to collapse wall-clock time.
    • Redundancy Elimination: Adding path-based filtering, shallow clones, and concurrency cancellation to stop wasteful runs.
    • Artifact Governance: Tightening retention policies and conditional uploads to slash storage costs.

    Why use this skill?

    Generic LLM prompting often results in "hallucinated" syntax or bash-heavy workarounds. This skill uses platform-native primitives (like GitLab's rules:changes or GitHub's cache: 'npm') to ensure your pipelines are idiomatic and maintainable. It doesn't just give you code; it provides a findings table with realistic savings estimates for runtime and storage.

    Output

    You receive a detailed audit report including a "before vs. after" comparison, a full optimized YAML configuration with inline documentation, and specific verification steps to measure your ROI.

    📖 Learn more: Best DevOps & Deployment Skills for Claude Code →

    Use Cases

    • Implement lockfile-keyed caching for faster dependency installation
    • Parallelize slow test suites using matrix strategies and sharding
    • Configure path-based triggers to skip CI for documentation-only changes
    • Reduce artifact storage costs by optimizing retention and upload rules

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    $9

    One-time