返回技能列表

polish-claw-project

pjt222
更新于 2 days ago
5 次查看
17
2
17
在 GitHub 上查看
automation

关于

This skill provides a structured 9-step workflow for developers to contribute security and code improvements to OpenClaw ecosystem projects. It emphasizes parallel auditing, false positive prevention, and cross-referencing findings against existing issues to ensure high-impact pull requests. Use it for systematic, convention-aware contributions to OpenClaw, NemoClaw, or NanoClaw repositories.

快速安装

Claude Code

推荐
主要方式
npx skills add pjt222/agent-almanac -a claude-code
插件命令备选方式
/plugin add https://github.com/pjt222/agent-almanac
Git 克隆备选方式
git clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/polish-claw-project

在 Claude Code 中复制并粘贴此命令以安装该技能

技能文档

Polish Claw Project

Structured workflow for contributing to OpenClaw ecosystem projects. Novel value in Steps 5-7: parallel audit, false positive prevention, cross-referencing findings against open issues to select high-impact contributions. Mechanical steps (fork, PR creation) delegate to existing skills.

When Use

  • Contributing to NVIDIA/OpenClaw, NVIDIA/NemoClaw, NVIDIA/NanoClaw, or similar Claw ecosystem repos
  • First-time contributions to unfamiliar open-source project with security-sensitive architecture
  • Want repeatable, auditable contribution workflow rather than ad-hoc fixes
  • After identifying Claw project that accepts external contributions (check CONTRIBUTING.md)

Inputs

  • Required: repo_url — GitHub URL of target Claw project (e.g. https://github.com/NVIDIA/NemoClaw)
  • Optional:
    • contribution_count — Number of contributions to aim for (default: 1-3)
    • focus — Preferred contribution type: security, tests, docs, bugs, any (default: any)
    • fork_org — GitHub org/user to fork into (default: authenticated user)

Steps

Step 1: Identify and Verify Target

Confirm project accepts external contributions and is actively maintained.

  1. Open repository URL. Read CONTRIBUTING.md, CODE_OF_CONDUCT.md, LICENSE
  2. Check recent commit activity (last 30 days) and open PR merge rate
  3. Verify project uses permissive or contribution-friendly license
  4. Read SECURITY.md or security policy if present — note responsible disclosure rules
  5. Identify primary language, test framework, CI system

Got: CONTRIBUTING.md exists. Commits within last 30 days. Clear contribution guidelines.

If fail: No CONTRIBUTING.md or no recent activity? Document why and stop. Stale projects rarely merge external PRs.

Step 2: Fork and Clone

Build working copy of repository.

  1. Fork: gh repo fork <repo_url> --clone
  2. Set upstream remote: git remote add upstream <repo_url>
  3. Verify: git remote -v shows both origin (fork) and upstream
  4. Sync: git fetch upstream && git checkout main && git merge upstream/main

Got: Local clone with both remotes configured and up to date.

If fail: Fork fails? Check GitHub authentication (gh auth status). Clone slow? Try --depth=1 for initial exploration.

Step 3: Explore Codebase

Build mental model of project architecture.

  1. Read README.md for architecture overview and project goals
  2. Identify entry points, core modules, public API surface
  3. Map test structure: where tests live, what framework, coverage level
  4. Note code style conventions: linter config, naming patterns, import style
  5. Check for Docker/container setup, CI configuration, deployment patterns

Got: Clear understanding of project structure, conventions, where contributions would fit.

If fail: Architecture unclear? Focus on specific subsystem rather than whole project.

Step 4: Read Open Issues

Survey existing issues to understand project needs and avoid duplicate work.

  1. List open issues: gh issue list --state open --limit 50
  2. Categorize by type: bugs, features, docs, security, good-first-issue
  3. Note issues labeled help wanted, good first issue, hacktoberfest
  4. Check for stale issues (>90 days open, no recent comments) — may be abandoned
  5. Read any linked PRs to understand attempted solutions

Got: Categorized list of unclaimed issues with type labels.

If fail: No open issues exist? Proceed to Step 5 — audit may uncover unlisted improvements.

Step 5: Parallel Audit

Run security and code quality audits in parallel. This is where novel findings emerge.

  1. Run security-audit-codebase skill against project root
  2. Simultaneously run review-codebase skill with scope quality
  3. Critical: verify each finding against project's threat model and architecture
    • "Hardcoded secret" in sandbox bootstrap script is not a vulnerability
    • Missing input validation on internal-only function is low severity
    • Dependency flagged as vulnerable may already be mitigated by project's architecture
  4. Rate verified findings: CRITICAL, HIGH, MEDIUM, LOW
  5. Document false positives with reasoning — informs Pitfalls for future runs

Got: List of verified findings with severity ratings and false positive annotations.

If fail: No findings emerge? Shift focus to test coverage gaps, documentation improvements, developer experience enhancements.

Step 6: Cross-Reference Findings

Map verified audit findings to open issues — core judgment step.

  1. For each verified finding, search open issues for related discussions
  2. Categorize each finding as:
    • Matches open issue — link finding to issue
    • New finding — no existing issue covers this
    • Already fixed in PR — check open PRs for in-progress fixes
  3. Prioritize findings matching existing issues (highest merge probability)
  4. For new findings, assess if maintainers would welcome fix based on project priorities

Got: Prioritized list with finding-to-issue mapping and merge probability assessment.

If fail: All findings already addressed? Return to Step 4. Look for documentation, test, or developer experience contributions.

Step 7: Select Contributions

Pick 1-3 contributions based on impact, effort, expertise.

  1. Score each candidate on:
    • Impact: How much does this improve project? (security > bugs > tests > docs)
    • Effort: Can this be done well in focused session? (prefer small, complete PRs)
    • Expertise: Does contributor have domain knowledge for this fix?
    • Merge probability: Does this match stated project priorities?
  2. Select top candidates (default: 1-3)
  3. For each, define: branch name, scope boundary, acceptance criteria, test plan

Got: 1-3 selected contributions with clear scope and acceptance criteria.

If fail: No contributions score well? Consider filing well-written issues instead of PRs.

Step 8: Implement

Create branch per contribution. Implement fix.

  1. For each contribution: git checkout -b fix/<description>
  2. Follow project conventions exactly (linter, naming, import style)
  3. Add or update tests covering change
  4. Run project's test suite. Verify all tests pass
  5. Run project's linter. Verify no new warnings
  6. Keep each PR focused — one logical change per branch

Got: Clean implementation with passing tests and no linter warnings.

If fail: Tests fail on pre-existing issues? Document them. Ensure PR doesn't introduce new failures.

Step 9: Create Pull Requests

Submit contributions following project's CONTRIBUTING.md.

  1. Push branch: git push origin fix/<description>
  2. Create PR using create-pull-request skill
  3. Reference related issue in PR body (e.g. "Fixes #123")
  4. Follow project's PR template if one exists
  5. Be responsive to reviewer feedback — iterate quickly

Got: PRs created, linked to issues, following project conventions.

If fail: PR creation fails? Check branch protection rules and contributor license agreements.

Checks

  1. All selected contributions implemented and submitted as PRs
  2. Each PR references related issue (if one exists)
  3. All project tests pass on each PR branch
  4. No false positive findings submitted as real issues
  5. PR descriptions follow project's CONTRIBUTING.md template

Pitfalls

  • False positive overclaim: Claw projects use sandbox architectures — "vulnerability" inside sandboxed environment may be by design. Always verify against project's threat model before reporting.
  • Digest/signature chain disruption: Claw projects often use verification chains for model integrity. Changes must preserve these chains or PR will be rejected.
  • Convention mismatch: Claw projects enforce strict style. Run project's own linter, not generic one. Match import ordering, docstring format, test patterns exactly.
  • Scope creep: 3 focused PRs merge faster than 1 sprawling PR. Keep each contribution atomic.
  • Stale fork: Always sync with upstream before starting work (git fetch upstream && git merge upstream/main).

See Also

GitHub 仓库

pjt222/agent-almanac
路径: i18n/caveman/skills/polish-claw-project
0
agentsagentskillsai-assisted-developmentclaude-codeskillsteams

相关推荐技能

content-collections

Content Collections 是一个 TypeScript 优先的构建工具,可将本地 Markdown/MDX 文件转换为类型安全的数据集合。它专为构建博客、文档站和内容密集型 Vite+React 应用而设计,提供基于 Zod 的自动模式验证。该工具涵盖从 Vite 插件配置、MDX 编译到生产环境部署的完整工作流。

查看技能

polymarket

这个Claude Skill为开发者提供完整的Polymarket预测市场开发支持,涵盖API调用、交易执行和市场数据分析。关键特性包括实时WebSocket数据流,可监控实时交易、订单和市场动态。开发者可用它构建预测市场应用、实施交易策略并集成实时市场预测功能。

查看技能

creating-opencode-plugins

该Skill帮助开发者创建OpenCode插件,用于接入命令、文件、LSP等25+种事件。它提供了插件结构、事件API规范和JavaScript/TypeScript实现模式,适合需要拦截操作、扩展功能或自定义事件处理的场景。开发者可通过它快速构建响应式模块来增强OpenCode AI助手的能力。

查看技能

sglang

SGLang是一个专为LLM设计的高性能推理框架,特别适用于需要结构化输出的场景。它通过RadixAttention前缀缓存技术,在处理JSON、正则表达式、工具调用等具有重复前缀的复杂工作流时,能实现极速生成。如果你正在构建智能体或多轮对话系统,并追求远超vLLM的推理性能,SGLang是理想选择。

查看技能