plugins/git-master/skills/github-actions-2025/SKILL.md
GitHub Actions 2025-2026 features and modernization. PROACTIVELY activate for: (1) 1 vCPU Linux runners (October 2025 public preview), (2) immutable releases for hardened distribution, (3) Node24 migration from Node20, (4) reusable workflows and composite actions, (5) workflow_dispatch with rich inputs, (6) artifact attestations and provenance, (7) ARC (Actions Runner Controller) for self-hosted Kubernetes, (8) larger runners and macOS Apple Silicon runners, (9) deployment environments and protection rules, (10) OIDC federation to AWS/Azure/GCP. Provides: workflow templates, runner-selection matrix, OIDC setup recipes, attestation patterns, and Node24 migration steps.
npx skillsauth add JosiahSiegel/claude-plugin-marketplace github-actions-2025Install this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
What: New lightweight runners optimized for automation tasks with lower cost.
Specs:
Ideal for:
NOT suitable for:
# .github/workflows/automation.yml
name: Lightweight Automation
on:
issues:
types: [opened, labeled]
jobs:
triage:
runs-on: ubuntu-latest-1-core # New 1 vCPU runner
timeout-minutes: 10 # Max 15 minutes
steps:
- name: Triage Issue
run: |
echo "Triaging issue..."
gh issue edit ${{ github.event.issue.number }} --add-label "needs-review"
# Before: Using 2 vCPU runner for simple task
jobs:
label:
runs-on: ubuntu-latest # 2 vCPU, higher cost
steps:
- name: Add label
run: gh pr edit ${{ github.event.number }} --add-label "reviewed"
# After: Using 1 vCPU runner (lower cost)
jobs:
label:
runs-on: ubuntu-latest-1-core # 1 vCPU, 50% cost reduction
timeout-minutes: 5
steps:
- name: Add label
run: gh pr edit ${{ github.event.number }} --add-label "reviewed"
What: Releases can now be marked immutable - assets and Git tags cannot be changed or deleted once released.
Benefits:
# Using GitHub CLI
gh release create v1.0.0 \
dist/*.zip \
--title "Version 1.0.0" \
--notes-file CHANGELOG.md \
--immutable
# Verify immutability
gh release view v1.0.0 --json isImmutable
# .github/workflows/release.yml
name: Create Immutable Release
on:
push:
tags:
- 'v*'
jobs:
release:
runs-on: ubuntu-latest
permissions:
contents: write
steps:
- name: Checkout
uses: actions/checkout@v4
- name: Build artifacts
run: npm run build
- name: Create Immutable Release
uses: actions/github-script@v7
with:
script: |
const fs = require('fs');
const tag = context.ref.replace('refs/tags/', '');
await github.rest.repos.createRelease({
owner: context.repo.owner,
repo: context.repo.repo,
tag_name: tag,
name: `Release ${tag}`,
body: fs.readFileSync('CHANGELOG.md', 'utf8'),
draft: false,
prerelease: false,
make_immutable: true # Mark as immutable
});
- name: Upload Release Assets
run: gh release upload ${{ github.ref_name }} dist/*.zip --clobber
# Organizational policy for immutable releases
name: Enforce Immutable Releases
on:
release:
types: [created]
jobs:
enforce-immutability:
runs-on: ubuntu-latest
if: "!github.event.release.immutable && startsWith(github.event.release.tag_name, 'v')"
steps:
- name: Fail if not immutable
run: |
echo "ERROR: Production releases must be immutable"
exit 1
What: GitHub Actions migrating from Node20 to Node24 in fall 2025.
Timeline:
Check Node version in actions:
# Old - Node20
jobs:
build:
runs-on: ubuntu-latest
steps:
- uses: actions/setup-node@v3
with:
node-version: '20' # Update to 24
# New - Node24
jobs:
build:
runs-on: ubuntu-latest
steps:
- uses: actions/setup-node@v4
with:
node-version: '24' # Current LTS
# Ensure runner supports Node24
jobs:
test:
runs-on: ubuntu-latest # Runner v2.328.0+ supports Node24
steps:
- name: Verify Node version
run: node --version # Should show v24.x.x
If you maintain custom actions:
// action.yml
runs:
using: 'node24' // Updated from 'node20'
main: 'index.js'
# Update dependencies
npm install @actions/core@latest
npm install @actions/github@latest
# Test with Node24
node --version # Ensure 24.x
npm test
What: Actions environments now available for all plans (public and private repos).
# .github/workflows/deploy.yml
name: Deploy to Production
on:
push:
branches: [main]
jobs:
deploy:
runs-on: ubuntu-latest
environment:
name: production
url: https://app.example.com
steps:
- name: Deploy
run: |
echo "Deploying to ${{ vars.DEPLOY_URL }}"
# Deployment steps...
Environment configuration:
What: Enhanced governance with explicit blocking and SHA pinning.
# .github/workflows/policy.yml
# Repository or organization settings
allowed-actions:
verified-only: true
# Explicitly block actions
blocked-actions:
- 'untrusted/action@*'
- 'deprecated-org/*'
# Require SHA pinning for security
require-sha-pinning: true
# Before: Version pinning (can be changed by action maintainer)
- uses: actions/checkout@v4
# After: SHA pinning (immutable)
- uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1
# Get commit SHA for specific version
gh api repos/actions/checkout/commits/v4.1.1 --jq '.sha'
# Or use action-security tool
npx pin-github-action actions/checkout@v4
# Output: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11
What: Workflows triggered by Copilot-authored events now require explicit approval.
# .github/workflows/copilot-automation.yml
name: Copilot PR Automation
on:
pull_request:
types: [opened]
jobs:
copilot-review:
runs-on: ubuntu-latest
# Copilot-generated PRs require approval
if: github.event.pull_request.user.login != 'github-copilot[bot]'
steps:
- name: Auto-review
run: gh pr review --approve
Manual approval required for Copilot PRs (same mechanism as fork PRs).
What: Artifacts moved to new architecture on February 1, 2025.
Breaking changes:
actions/upload-artifact@v1-v2 retired March 1, 2025actions/upload-artifact@v4+# Old (Retired)
- uses: actions/upload-artifact@v2
with:
name: build-artifacts
path: dist/
# New (Required)
- uses: actions/upload-artifact@v4
with:
name: build-artifacts
path: dist/
retention-days: 30
What: windows-2019 runner image fully retired June 30, 2025.
# Old
jobs:
build:
runs-on: windows-2019 # Retired
# New
jobs:
build:
runs-on: windows-2022 # Current
# Or windows-latest (recommended)
What: New actions_inbound section in meta API for network configuration.
# Get network requirements for self-hosted runners
curl https://api.github.com/meta | jq '.actions_inbound'
# Configure firewall rules based on response
{
"domains": [
"*.actions.githubusercontent.com",
"*.pkg.github.com"
],
"ip_ranges": [
"140.82.112.0/20",
"143.55.64.0/20"
]
}
# Use 1 vCPU for lightweight tasks
jobs:
label-management:
runs-on: ubuntu-latest-1-core
timeout-minutes: 5
# Use standard runners for builds/tests
build:
runs-on: ubuntu-latest
# Always mark production releases as immutable
- name: Create Release
run: gh release create $TAG --immutable
# Pin actions to SHA, not tags
- uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11
- uses: actions/setup-node@60edb5dd545a775178f52524783378180af0d1f8
# Use latest Node version
- uses: actions/setup-node@v4
with:
node-version: '24'
# Use environments for deployments
jobs:
deploy:
environment: production
# Requires approval, wait timer, branch restrictions
1 vCPU runner timeout:
# Ensure task completes within 15 minutes
jobs:
task:
runs-on: ubuntu-latest-1-core
timeout-minutes: 10 # Safety margin
Node24 compatibility issues:
# Test locally with Node24
nvm install 24
nvm use 24
npm test
Artifact upload failures:
# Use v4 of artifact actions
- uses: actions/upload-artifact@v4 # Not v1/v2
development
This skill should be used when the user asks to train, debug, scale, or improve ML models. PROACTIVELY activate for: (1) PyTorch, TensorFlow/Keras, JAX, Flax, Hugging Face Trainer/Accelerate training loops, (2) distributed training, DDP/FSDP/DeepSpeed, TPU/GPU setup, (3) mixed precision AMP/bf16, gradient accumulation, checkpointing, seeding, (4) overfitting, imbalance, loss functions, regularization, LR schedules, warmup, (5) memory optimization, gradient checkpointing, offloading, quantization-aware training. Provides: reproducible training best practices across deep learning and classical ML.
development
This skill should be used when the user asks to productionize, track, version, govern, monitor, or automate ML systems. PROACTIVELY activate for: (1) MLflow, Weights & Biases, Neptune, Comet, ClearML experiment tracking, (2) model registry, model versioning, artifact lineage, reproducibility, (3) Kubeflow, SageMaker Pipelines, Vertex AI Pipelines, Azure ML pipelines, Databricks workflows, (4) CI/CD, continuous training/evaluation, A/B tests, canary/shadow deployments, (5) drift detection, model monitoring, data validation, responsible AI governance. Provides: end-to-end MLOps architecture and operational safeguards.
development
This skill should be used when the user asks to optimize, export, serve, compress, or accelerate ML inference. PROACTIVELY activate for: (1) latency, throughput, p95/p99, batching, concurrency, KV cache, memory, or cost issues, (2) quantization INT8/INT4, GPTQ, AWQ, bitsandbytes, pruning, sparsity, distillation, (3) ONNX export, ONNX Runtime, TensorRT, TorchScript, torch.compile, XLA, OpenVINO, Core ML, TFLite, (4) Triton, TorchServe, TF Serving, BentoML, Seldon, KServe configuration, (5) edge deployment, CPU/GPU/TPU/Inferentia serving. Provides: hardware-aware inference optimization and safe benchmarking.
testing
This skill should be used when the user asks to tune hyperparameters, run sweeps, optimize search spaces, or use AutoML. PROACTIVELY activate for: (1) Optuna, Ray Tune, FLAML, AutoGluon, Hyperopt, Nevergrad, KerasTuner, W&B sweeps, (2) grid search, random search, Bayesian optimization, TPE, Gaussian processes, evolutionary search, (3) ASHA, Hyperband, successive halving, multi-fidelity optimization, population-based training, (4) learning-rate finder, batch-size search, early stopping, pruning, (5) reproducible sweep design and experiment analysis. Provides: budget-aware hyperparameter search strategy.