bundled-skills/openclaw-github-repo-commander/SKILL.md
7-stage super workflow for GitHub repo audit, cleanup, PR review, and competitor analysis
npx skillsauth add FrancoStino/opencode-skills-antigravity openclaw-github-repo-commanderInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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A structured 7-stage super workflow for comprehensive GitHub repository management. This skill automates repository auditing, cleanup, competitor benchmarking, and optimization — turning a messy repo into a clean, well-documented, production-ready project.
/super-workflow or /openclaw-github-repo-commander on a repo URLClone the target repository, define success criteria, and establish baseline metrics.
Run scripts/repo-audit.sh <repo-path> from this skill directory — automated read-only checks for:
ghp_, sk-, AKIA, etc.)node_modules/ or build artifacts.gitignore coverageDeep manual review beyond automation: content quality, documentation consistency, structural issues, version mismatches.
Search GitHub for similar repositories. Compare documentation standards, feature coverage, star counts, and community adoption.
Consolidate all findings into a prioritized action plan (P0 critical / P1 important / P2 nice-to-have).
Execute the plan: delete low-value files, fix security issues, upgrade documentation, add CI workflows, update changelogs.
Re-run the audit script (target: 7/7 PASS), verify all changes, push to GitHub, and deliver a full report.
/openclaw-github-repo-commander https://github.com/owner/my-repo
Runs all 7 stages and produces a detailed before/after report.
Clean up my GitHub repo — remove junk files, fix secrets, add .gitignore
Compare my skill repo with the top 5 similar repos on GitHub
chore:, fix:, docs:pr_todo.json file for pending reviewer requestsnode_modules/ or .env files.github/workflows/ to avoid false positivesgh CLI operations use the user's existing authentication — no credentials are stored by this skillOriginally contributed by @wd041216-bit in PR #340. No standalone upstream repository is currently available for this skill.
License: MIT | Version: 4.0.0
tools
Authorized security assessment of LLM applications and AI agents: prompt injection, tool abuse, RAG exposure, memory poisoning, system-prompt extraction, and agent-compliance engineering per OWASP LLM/ASI Top 10.
development
Builds two parameterized UI modes—流光溢彩白 (iridescent white) and 五彩斑斓黑 (colorful black)—with OKLCH, WebGL/CSS fallback, vision gating, screenshot QA, and total/per-color intensity reports. Use when a UI request names either mode or needs measured color parameters.
tools
Delegate coding tasks to the Kimi Code CLI (`kimi`) only when the user explicitly requests it, while the orchestrator retains review and landing responsibility.
development
Front-end JavaScript reverse engineering: locate signature chains, analyze encrypted request parameters, sample runtime behavior, and reproduce logic locally in Node for evidence-based output.