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Ci local

Skill mgiovani/cc-arsenal/skills/ci-local

45 production-grade AI agent skills for real dev workflows. Code review, shipping, docs, git. Works with any skill-compatible agent.

Install
npx -y skills add mgiovani/cc-arsenal --skill ci-local

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One thing to look at

  • 6 stars6 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Run the checks a GitHub Actions workflow would run, locally, when Actions is unavailable or out of quota. Parses .github/workflows/*.yml, extracts the jobs/steps that gate merges (lint, typecheck, test, build), translates them to local commands respecting the workflow's pinned node/python versions and env, executes them sequentially, and reports a parity table of what passed locally vs. what can't be replicated (service containers, secrets, matrix dimensions) and why. Activates on "CI quota", "Actions is down/unavailable", "run CI locally", "verify like CI would", "run the pipeline on my machine", or a pre-push request to check a branch the way CI checks it. Not for generating a new workflow file (use ci-generate), not for debugging why a specific CI run failed on GitHub (use fix-bug or review-code), and not for the release/hotfix gating process itself (use gitflow) — this skill only produces the local stand-in when the real thing isn't reachable.

SKILL.md

6.9 KB, as published. Nobody here has run it

CI Local

Reproduce a GitHub Actions run on the local machine. The workflow YAML is the spec — read it, don't guess at what "the lint step" or "the test step" means.

Scope

GitHub Actions only (.github/workflows/*.yml). If the repo uses GitLab CI, CircleCI, or Jenkins instead, say so and stop — no translation layer exists for those yet (add one if it comes up twice, not speculatively).

Phase 1: Find the merge-gating jobs

  1. If invoked with [workflow-file] and/or --job name, skip the glob — read only that file, and if --job is given, extract only that job. Otherwise Glob for .github/workflows/*.yml (and .yaml). If none exist, tell the user there's no workflow to mirror and stop.
  2. Read each file. A job gates merges if its workflow triggers on pull_request or push to a protected branch — ignore jobs that only run on schedule, workflow_dispatch, or release unless the user asks for those specifically.
  3. For a multi-file or multi-job repo, use a haiku Explore subagent to read all workflow files in parallel and return a structured list of: job name, trigger, runs-on, steps (with uses/run/env/working-directory), services:, strategy.matrix, and any ${{ secrets.* }} references. Keep this out of the main thread — workflow YAML is verbose and you only need the extracted summary. No subagent tool available? Read the workflow files directly and extract the same summary inline.

Phase 2: Translate steps to local commands

Walk the steps in order and translate each one. Do not invent a generic lint && test && build — use exactly what the workflow does.

Workflow stepLocal translation
actions/checkoutno-op — you're already in the working tree
actions/setup-node with node-version: Xfnm use X (or nvm use X) before the next steps; if neither is installed, warn and continue on whatever node -v reports
actions/setup-python with python-version: Xuv python pin X / uv run --python X ...; same fallback-and-warn if uv isn't available
run: <cmd> with a working-directory: or env: blockrun <cmd> from that directory with those env vars exported for just that command
cache steps (actions/cache)no-op — local disk cache already exists
a run: step gated by if: on OS or eventskip if the condition can't hold locally (e.g. runs-on: windows-latest step on a Mac), and say so

If no explicit version is pinned in the workflow, check .nvmrc / package.json#engines.node or .python-version / pyproject.toml#requires-python before falling back to whatever's on PATH.

Can't be replicated — flag, don't fake:

  • services: (Postgres, Redis, etc.) — note the service and image; only attempt it if Docker is available and the user wants the extra step, otherwise mark the steps that depend on it as skipped.
  • ${{ secrets.* }} — check if a local .env supplies the same variable name; if not, mark the step as skipped with the missing secret name, never substitute a fake value.
  • strategy.matrix — run the one combination that matches the local machine (current node/python/OS); list the other matrix entries as not covered.

Phase 3: Execute sequentially

Run the translated commands via Bash, in the same order the workflow declares them, stopping to report clearly the moment one fails (don't silently keep going past a failed lint step and call the run "done"). Capture stdout/stderr for the report.

Phase 4: Report the parity table

CI Local Parity — <workflow file>, job "<job name>"

Step                  Local result     Notes
---------------------------------------------------------------
checkout              n/a              already in working tree
setup-node 20         ok               fnm use 20
lint (eslint)          PASS
typecheck (tsc)        PASS
test (vitest)           FAIL            2 tests failing, see output above
build                  SKIPPED         not run, blocked by failing test
postgres service       NOT REPLICABLE  no service container locally (Docker not requested)
deploy (secrets.AWS_*)  NOT REPLICABLE  secret not present in .env

Any version-fallback warning from Phase 2 (pinned node/python version unavailable, falling back to whatever's on PATH) must surface as a caveat/NOT REPLICABLE note in this parity table — never absorbed into a PASS.

Every row's result comes from a command you actually ran this session — never write PASS, FAIL, or a test count you didn't observe in the Phase 3 output.

State plainly at the end whether the branch would pass the real CI gate, and what's still unverified because it couldn't run locally.

Examples

Targeted job, --job lint given: skip the glob, read only the named job's steps from the file the user pointed at, translate and run just those, report a parity table scoped to that one job.

Python repo, no pinned version in the workflow: actions/setup-python has no python-version: key → check pyproject.toml#requires-python, find >=3.11, run uv run --python 3.11 pytest. Note the fallback source in the parity table ("version from pyproject.toml, not workflow"), don't silently treat it as pinned.

Matrix build, strategy.matrix: node: [18, 20, 22]: run once on whatever fnm/nvm resolves locally (say 20), mark 18 and 22 as NOT REPLICABLE — matrix entry not run locally in the table instead of guessing they'd also pass.

Notes

  • This is read-only with respect to git — no commits, no pushes, no workflow file edits. Installing dependencies (npm ci, uv sync, etc.) as part of a step is expected and fine.
  • If the same repo asks for this repeatedly, that's a signal to fix the actual CI quota/outage, not to keep leaning on the local stand-in — mention that once, don't nag.

Keep looking

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