Skill: cypherm/oss-pilot (version 2.0.2)

--- name: oss-contribution-system description: End-to-end open-source GitHub contribution automation system. Discover high-value issues, implement fixes, open quality PRs, monitor CI/review status, and learn from each contribution. Uses gh CLI for GitHub API access, git for version control, and stores workspace-local data in ./oss-pilot-data/ for profiles and PR context. Triggers on "oss discover", "oss auto", "oss pr", "oss check", "find issues", "what should I work on", "next PR", "auto PR", "review PR", "check PRs", "morning check". user_invocable: true metadata: openclaw: requires: bins: - gh - git --- # OSS Contribution System A complete system for contributing to open-source repos. Four skills work together in a learning loop --each contribution makes the next one better. ## Quick Start 1. **First time?** Just say: `oss discover <repo-url-or-name>` - The system will create a profile, check repo openness, and find issues for you. 2. **Found an issue?** Say: `oss auto <repo> #12345` - End-to-end: implement -> open PR -> respond to bots -> ping maintainer. 3. **Already have a PR?** Say: `oss check <repo>` - Checks CI, bot comments, stale status, and takes action. 4. **Want a quality review?** Say: `oss pr review <repo> #12345` - Root cause analysis, diff check, description quality, bot response strategy. ## How the System Works ``` discover --> auto --> pr --> check --> retrospective ^ ^ | | | +-------+ | | (human review loop) | | v | profile grows (lessons, patterns) | | +---- checks archived history -------------+ (avoid past mistakes) ``` **Profile** (`./oss-pilot-data/profiles/<repo>.md`): Stores repo-specific knowledge --build commands, maintainer styles, bot behavior, lessons learned. Grows with each contribution. See `_template.md` for the schema. **Context files** (`./oss-pilot-data/context/pr-<repo>-<N>.md`): Track each PR's approach, bot decisions, and outcome. Archived after merge/close for future reference. ## The Four Skills ### oss-discover (find.md) Find high-value issues with the highest merge probability. - Checks repo openness (external contributor merge rate) - Checks issue velocity (how fast issues get claimed) - Scans 8 sources: high-signal labels -> bugs -> CI failures -> reclaimable PRs -> merged PR gaps -> scoped modules -> area merge rate -> codebase cleanup - Verifies bugs still exist, checks comments for signals, evaluates fix feasibility **Read: `discover.md`** ### oss-auto (auto.md) One command from issue to opened PR. Orchestrates discover + pr. - Cold start: auto-creates profile for new repos - Feasibility check -> implement -> open PR -> respond to bots -> mark ready -> ping maintainer - Auto-detects build tooling (Node/Python/Go/Rust/Make) - Reads CONTRIBUTING.md and CLAUDE.md for repo conventions **Read: `auto.md`** ### oss-pr (pr.md) Quality gate for PRs. Validates before requesting review. - Root cause analysis (right layer? blast radius? semantic contracts?) - Common mistake patterns and anti-patterns - PR description with "What did NOT change" and "What I Did NOT Verify" - Bot response strategy (accept/decline/repeat handling) - CI failure triage template **Read: `pr.md`** ### oss-check (check.md) Morning check-in for all pending PRs. - CI/bot/stale status monitoring - Retrospective on merged/closed PRs (writes Outcome + routes lessons) - Maintenance: prunes stale lessons, archives old context files - Handles fork PR CI skipping (normal for external contributors) **Read: `check.md`** ## Prerequisites - `gh` CLI installed and authenticated (`gh auth status`) - GitHub account with a fork of the target repo - Optional: local clone for codebase scanning (Source 8) ## Security Model This skill instructs the agent to run build, lint, and test commands (e.g., `pnpm install`, `make`, `cargo test`) from the target repository. This is inherent to contribution automation --you cannot validate a fix without running the repo's toolchain. **Threat surface**: If the target repo contains malicious build scripts (e.g., postinstall hooks), those commands execute on your machine. This is the same risk as manually cloning a repo and running `npm install`. **How risk is managed**: - **User trust boundary**: You choose which repo to target. The skill never picks repos autonomously. - **Runtime gating**: OpenClaw's exec approval system prompts before executing shell commands. The skill issues instructions; the runtime decides whether to run them. - **Scope checkpoint**: The skill stops and asks before committing to changes >5 files or >200 lines. **Recommended hardening**: - Run inside a container (`openclaw --container <name>`) or VM when targeting unfamiliar repos. - Review the repo's `package.json` scripts / `Makefile` targets before first run. - Use a dedicated GitHub account for automation if you prefer isolation. ## Data Directories The system creates and manages these directories: - `./oss-pilot-data/profiles/` --one profile per repo - `./oss-pilot-data/context/` --active PR context files - `./oss-pilot-data/context/_archived/` --completed PR context files (for learning)


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)