Agent skill
gh-fix-ci
Use when a user asks to debug or fix failing GitHub PR checks that run in GitHub Actions; use `gh` to inspect checks and logs, summarize failure context, draft a fix plan, and implement only after explicit approval. Treat external providers (for example Buildkite) as out of scope and report only the details URL.
Install this agent skill to your Project
npx add-skill https://github.com/foryourhealth111-pixel/Vibe-Skills/tree/main/bundled/skills/gh-fix-ci
SKILL.md
Gh Pr Checks Plan Fix
Overview
Use gh to locate failing PR checks, fetch GitHub Actions logs for actionable failures, summarize the failure snippet, then propose a fix plan and implement after explicit approval.
- If a plan-oriented skill (for example
create-plan) is available, use it; otherwise draft a concise plan inline and request approval before implementing.
Prereq: authenticate with the standard GitHub CLI once (for example, run gh auth login), then confirm with gh auth status (repo + workflow scopes are typically required).
Inputs
repo: path inside the repo (default.)pr: PR number or URL (optional; defaults to current branch PR)ghauthentication for the repo host
Quick start
python "<path-to-skill>/scripts/inspect_pr_checks.py" --repo "." --pr "<number-or-url>"- Add
--jsonif you want machine-friendly output for summarization.
Workflow
- Verify gh authentication.
- Run
gh auth statusin the repo. - If unauthenticated, ask the user to run
gh auth login(ensuring repo + workflow scopes) before proceeding.
- Run
- Resolve the PR.
- Prefer the current branch PR:
gh pr view --json number,url. - If the user provides a PR number or URL, use that directly.
- Prefer the current branch PR:
- Inspect failing checks (GitHub Actions only).
- Preferred: run the bundled script (handles gh field drift and job-log fallbacks):
python "<path-to-skill>/scripts/inspect_pr_checks.py" --repo "." --pr "<number-or-url>"- Add
--jsonfor machine-friendly output.
- Manual fallback:
gh pr checks <pr> --json name,state,bucket,link,startedAt,completedAt,workflow- If a field is rejected, rerun with the available fields reported by
gh.
- If a field is rejected, rerun with the available fields reported by
- For each failing check, extract the run id from
detailsUrland run:gh run view <run_id> --json name,workflowName,conclusion,status,url,event,headBranch,headShagh run view <run_id> --log
- If the run log says it is still in progress, fetch job logs directly:
gh api "/repos/<owner>/<repo>/actions/jobs/<job_id>/logs" > "<path>"
- Preferred: run the bundled script (handles gh field drift and job-log fallbacks):
- Scope non-GitHub Actions checks.
- If
detailsUrlis not a GitHub Actions run, label it as external and only report the URL. - Do not attempt Buildkite or other providers; keep the workflow lean.
- If
- Summarize failures for the user.
- Provide the failing check name, run URL (if any), and a concise log snippet.
- Call out missing logs explicitly.
- Create a plan.
- Use the
create-planskill to draft a concise plan and request approval.
- Use the
- Implement after approval.
- Apply the approved plan, summarize diffs/tests, and ask about opening a PR.
- Recheck status.
- After changes, suggest re-running the relevant tests and
gh pr checksto confirm.
- After changes, suggest re-running the relevant tests and
Bundled Resources
scripts/inspect_pr_checks.py
Fetch failing PR checks, pull GitHub Actions logs, and extract a failure snippet. Exits non-zero when failures remain so it can be used in automation.
Usage examples:
python "<path-to-skill>/scripts/inspect_pr_checks.py" --repo "." --pr "123"python "<path-to-skill>/scripts/inspect_pr_checks.py" --repo "." --pr "https://github.com/org/repo/pull/123" --jsonpython "<path-to-skill>/scripts/inspect_pr_checks.py" --repo "." --max-lines 200 --context 40
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
pufferlib
This skill should be used when working with reinforcement learning tasks including high-performance RL training, custom environment development, vectorized parallel simulation, multi-agent systems, or integration with existing RL environments (Gymnasium, PettingZoo, Atari, Procgen, etc.). Use this skill for implementing PPO training, creating PufferEnv environments, optimizing RL performance, or developing policies with CNNs/LSTMs.
fluidsim
Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis.
metabolomics-workbench-database
Access NIH Metabolomics Workbench via REST API (4,200+ studies). Query metabolites, RefMet nomenclature, MS/NMR data, m/z searches, study metadata, for metabolomics and biomarker discovery.
build-error-resolver
Compatibility alias for build-specific error resolution. Use this when VCO routes to build-error-resolver but the upstream agent is unavailable in the current runtime.
geniml
This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.
zinc-database
Access ZINC (230M+ purchasable compounds). Search by ZINC ID/SMILES, similarity searches, 3D-ready structures for docking, analog discovery, for virtual screening and drug discovery.
Didn't find tool you were looking for?