Evaluate and address a GitHub pull request review locally. Use when a PR review contains inline comments, suggestions, or requested changes that need to be implemented in the local workspace. Covers fetching review threads, triaging by severity, applying code fixes, running tests, and optionally replying to or resolving review threads.
Use when an open apijack PR (base `dev`) is mid-review-cycle and needs to be driven to `first pass reviewed`. Picks up cold from any in-flight state — `changes requested`, `review in progress`, `needs review`, or freshly opened. Covers both interactive and `--non-interactive` (cron) modes.
Automated code review analyzing diffs for test coverage, code quality, architecture conformance, and security. Produces structured findings and optionally creates beads for issues found. Use when user says "review code", "code review", "review my changes", "check this branch", "/code-review", or wants automated quality analysis before merging.
AI 扮演你的 Leader，用大厂管理思维 push 你成长。支持方案 Review、1-on-1 绩效谈话、KPI 季、复盘拷问、对齐会等场景。支持阿里/字节/腾讯/华为/美团/小米等大厂味道，支持自定义 Leader 人设。核心链路：AI（扮演 Leader）→ 用户。触发词：/leader, /review, /1on1, /kpi, /qbr, /flavor, /create-leader。
Multi-LLM peer review — send plans, ideas, or code to GPT (via OpenAI Codex CLI) and Gemini (via Gemini CLI) for structured peer review with cross-examination, then cherry-pick feedback. Decision Packet v2 with tiered output (Ship Blocker / Before Next Sprint / Backlog), dependency arrows, effort estimates, conflict flags, and JSON export. Tie-breaker model resolves HIGH CONFIDENCE deadlocks. Supports review, idea, redteam, debate, premortem, advocate, refactor, deploy, api, perf, diff, quick, help, and history modes. Supports parallel multi-mode dispatch (--modes redteam,deploy,perf) with collision detection. Use this skill whenever the user wants a second opinion from other AI models, wants to brainstorm with multiple perspectives, needs adversarial analysis, wants to stress-test a plan, review a code diff, get deployment readiness feedback, API design review, performance analysis, or mentions peer review, brainstorm, or multi-LLM feedback. Supports --rounds N, --verbose, --quiet, --gpt-model, --gemini-model, --steelman, --iterate, --json, and --modes flags. Falls back to GitHub Copilot CLI if Codex CLI is unavailable.
skill-sample/ ├─ SKILL.md ⭐ Required: skill entry doc (purpose / usage / examples / deps) ├─ manifest.sample.json ⭐ Recommended: machine-readable metadata (index / validation / autofill) ├─ LICENSE.sample ⭐ Recommended: license & scope (open source / restriction / commercial) ├─ scripts/ │ └─ example-run.py ✅ Runnable example script for quick verification ├─ assets/ │ ├─ example-formatting-guide.md 🧩 Output conventions: layout / structure / style │ └─ example-template.tex 🧩 Templates: quickly generate standardized output └─ references/ 🧩 Knowledge base: methods / guides / best practices ├─ example-ref-structure.md 🧩 Structure reference ├─ example-ref-analysis.md 🧩 Analysis reference └─ example-ref-visuals.md 🧩 Visual reference
More Agent Skills specs Anthropic docs: https://agentskills.io/home
├─ ⭐ Required: YAML Frontmatter (must be at top) │ ├─ ⭐ name : unique skill name, follow naming convention │ └─ ⭐ description : include trigger keywords for matching │ ├─ ✅ Optional: Frontmatter extension fields │ ├─ ✅ license : license identifier │ ├─ ✅ compatibility : runtime constraints when needed │ ├─ ✅ metadata : key-value fields (author/version/source_url...) │ └─ 🧩 allowed-tools : tool whitelist (experimental) │ └─ ✅ Recommended: Markdown body (progressive disclosure) ├─ ✅ Overview / Purpose ├─ ✅ When to use ├─ ✅ Step-by-step ├─ ✅ Inputs / Outputs ├─ ✅ Examples ├─ 🧩 Files & References ├─ 🧩 Edge cases ├─ 🧩 Troubleshooting └─ 🧩 Safety notes
Skill files are scattered across GitHub and communities, difficult to search, and hard to evaluate. SkillWink organizes open-source skills into a searchable, filterable library you can directly download and use.
We provide keyword search, version updates, multi-metric ranking (downloads / likes / comments / updates), and open SKILL.md standards. You can also discuss usage and improvements on skill detail pages.
Quick Start:
Import/download skills (.zip/.skill), then place locally:
~/.claude/skills/ (Claude Code)
~/.codex/skills/ (Codex CLI)
One SKILL.md can be reused across tools.
Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.
A skill is a reusable capability package, usually including SKILL.md (purpose/IO/how-to) and optional scripts/templates/examples.
Think of it as a plugin playbook + resource bundle for AI assistants/toolchains.
Skills use progressive disclosure: load brief metadata first, load full docs only when needed, then execute by guidance.
This keeps agents lightweight while preserving enough context for complex tasks.
Use these three together:
Note: file size for all methods should be within 10MB.
Typical paths (may vary by local setup):
One SKILL.md can usually be reused across tools.
Yes. Most skills are standardized docs + assets, so they can be reused where format is supported.
Example: retrieval + writing + automation scripts as one workflow.
Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.
Most common reasons:
We try to avoid that. Use ranking + comments to surface better skills:
