.claude/skills/watch-ci/SKILL.md
Watch GitHub Actions CI status for the current commit until completion. Use after pushing changes to monitor build results.
npx skillsauth add codervisor/lean-spec watch-ciInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Poll the GitHub Actions CI pipeline for the current HEAD commit until all jobs finish.
The gh CLI is not available in the Claude VM. Use the GitHub REST API via curl.
The repo is codervisor/lean-spec.
Get the current commit SHA and branch:
SHA=$(git rev-parse HEAD)
BRANCH=$(git branch --show-current)
echo "Watching CI for commit $SHA on branch $BRANCH"
Find the workflow run matching our exact commit. The API returns runs newest-first; filter by head_sha. If the run hasn't appeared yet (GitHub can take a few seconds), retry up to 5 times with 10s waits:
curl -sH "Accept: application/vnd.github+json" \
"https://api.github.com/repos/codervisor/lean-spec/actions/runs?branch=$BRANCH&head_sha=$SHA&per_page=1" \
| python3 -c "
import json, sys
data = json.load(sys.stdin)
runs = data.get('workflow_runs', [])
if not runs:
print('NO_RUNS'); sys.exit()
r = runs[0]
print(f'RUN_ID={r[\"id\"]}')
print(f'Status: {r[\"status\"]} Conclusion: {r.get(\"conclusion\") or \"pending\"} Commit: {r[\"head_sha\"][:8]}')"
Poll jobs until all complete (every 60s for Rust builds which take ~8-10 min):
curl -sH "Accept: application/vnd.github+json" \
"https://api.github.com/repos/codervisor/lean-spec/actions/runs/$RUN_ID/jobs" \
| python3 -c "
import json, sys
data = json.load(sys.stdin)
for j in data.get('jobs', []):
steps = [s for s in j.get('steps', []) if s['status'] == 'in_progress']
step_info = f' -> {steps[0][\"name\"]}' if steps else ''
print(f'{j[\"name\"]:40} {j[\"status\"]:12} {j.get(\"conclusion\") or \"\"}{step_info}')"
On failure, fetch the failed job logs to diagnose:
curl -sH "Accept: application/vnd.github+json" \
"https://api.github.com/repos/codervisor/lean-spec/actions/runs/$RUN_ID/jobs" \
| python3 -c "
import json, sys
data = json.load(sys.stdin)
for j in data.get('jobs', []):
if j.get('conclusion') == 'failure':
print(f'FAILED: {j[\"name\"]} (id: {j[\"id\"]})')
for s in j.get('steps', []):
if s.get('conclusion') == 'failure':
print(f' Step: {s[\"name\"]}')"
Give the user a brief status update each poll cycle. On completion, summarize:
development
The spec-coding methodology for AI-assisted development. Use when planning features, creating/refining/implementing/verifying specs, or organising a project. Works with whatever spec backend your team already uses — local markdown, GitHub Issues, Azure DevOps, Jira — by delegating platform-specific details to a LeanSpec adapter.
development
The spec-coding methodology for AI-assisted development. Use when planning features, creating/refining/implementing/verifying specs, or organising a project. Works with whatever spec backend your team already uses — local markdown, GitHub Issues, Azure DevOps, Jira — by delegating platform-specific details to a LeanSpec adapter.
development
Run multiple AI coding agent sessions in parallel using git worktrees — each agent isolated in its own worktree, working on a separate branch. Use this skill whenever the user wants to: run two or more AI agents simultaneously on different features or bugs, set up isolated agent workspaces in the same repo, push parallel branches to GitHub and open/update PRs, coordinate between concurrent agent sessions, or clean up after merging. Triggers on: "parallel agents", "multiple agent sessions", "git worktree", "run agents in parallel", "work on two things at once", "isolated agent workspace", "spin up another agent", or any request involving simultaneous AI-assisted development streams.
development
Development workflows, commands, publishing, CI/CD, changelog management, and contribution guidelines for LeanSpec. Use when contributing code, fixing bugs, setting up dev environment, running tests or linting, working with the monorepo structure, looking up build/dev/test/publish/format/lint commands, preparing releases, publishing to npm, bumping versions, syncing package versions, testing dev builds, troubleshooting npm distribution, updating changelogs, triggering CI/CD workflows, monitoring build status, debugging failed runs, managing artifacts, checking CI before releases, or researching AI agent runners. Triggers include any development, scripting, publishing, CI/CD, changelog, or runner research task in this project.