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deploy-log-doctorlisted

Diagnose failed build and deploy logs from Vercel, Netlify, Cloudflare Pages, or GitHub Actions. Use this whenever the user pastes a build log, says a deploy failed, mentions 'build error', 'deployment failed', 'works locally but not in production', or shows any CI output containing an error — even if they don't ask for a diagnosis explicitly. Runs fully offline — no API keys, no network, no credentials.
Starr-del/deploy-preflight · ★ 0 · DevOps & Infrastructure · score 70
Install: claude install-skill Starr-del/deploy-preflight
# deploy-log-doctor Part of **deploy-preflight** — offline deploy-safety skills. Every script is stdlib-only Python 3.8+; nothing leaves the machine. Run the classifier on the log first, then interpret: ```bash python3 scripts/diagnose_log.py <logfile> # or pipe: cat log | python3 scripts/diagnose_log.py - python3 scripts/diagnose_log.py <logfile> --json # structured output ``` The script matches 11 curated failure signatures (missing env vars, case-sensitive imports, Node version mismatches, OOM, lockfile drift, peer-dep conflicts, Prisma generate, and more) and emits the root cause plus numbered fix steps. Workflow: 1. Save the user's log to a file (or pipe it) and run the script. 2. If it returns a diagnosis, walk the user through the fix steps, adapting them to the user's actual framework and platform. 3. If it returns nothing (exit 2), the log is probably truncated above the real error — ask for the section around the first ERROR line and rerun. 4. After fixing, suggest the rollback-readiness skill to catch the next failure class before it happens. Exit codes: 0 diagnosed, 2 no signature matched. All paths below are relative to this skill's directory (deploy-log-doctor/).