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GitHub Actions Speed and Cost Optimizer

aka “Actions Accelerator”

Cut your GitHub Actions bill and build time in half

Analyzes your GitHub Actions workflows for speed and cost optimizations: unnecessary steps, missing caches, serial jobs that could parallelize, oversized runners, and workflow duplication across repos.

House RecipeWork2 min
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INGREDIENTS

🐙GitHub

PROMPT

Create a skill called "Actions Accelerator". Optimize GitHub Actions workflows for speed and cost: 1. Read all workflow YAML files in .github/workflows/ 2. Analyze each workflow for: - Missing dependency caches (npm, pip, gradle, cargo, etc.) - Steps that could be parallelized (independent jobs running sequentially) - Unnecessary checkout or setup steps - Missing `paths` or `paths-ignore` filters - Oversized runner selections - Missing `concurrency` groups (redundant runs not being cancelled) - Duplicate logic across workflows that could be extracted into reusable workflows 3. If GitHub CLI is available, analyze recent run history: - Average and p95 workflow duration - Which steps take the longest - Failure rates by step - Monthly minutes consumption and estimated cost 4. Generate optimized workflow files with all improvements applied 5. Estimate time and cost savings from each optimization Explain each change with before/after comparisons.

How It Works

GitHub Actions minutes cost money, and slow workflows cost developer time.

This skill reviews your workflow YAML and run history to find both.

What You Get

  • Workflow analysis: unnecessary steps, missing caches, serial bottlenecks
  • Cache optimization: npm/yarn/pip/gradle caches properly configured
  • Runner right-sizing: are you using ubuntu-latest when a smaller runner would do?
  • Parallelization opportunities: jobs that could run concurrently
  • Duplicate workflow detection across repos
  • Cost estimation and savings projections
  • Optimized workflow YAML with all improvements applied

Setup Steps

  1. Point your Claw at a repo or organization
  2. Let it analyze workflow files and recent run history
  3. Review the optimization suggestions
  4. Apply the optimized workflow YAML

Tips

  • Dependency caching is the single biggest win for most workflows
  • Use `paths` filters to skip workflows when irrelevant files change
  • Matrix builds can test across versions in parallel instead of sequentially
  • Consider self-hosted runners for heavy workloads (cost break-even is usually ~2000 min/month)
  • Use `concurrency` groups to cancel redundant runs on the same branch
Tags:#ci-cd#github-actions#optimization#devops

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