Interactive visual canvas for structured communication between agent and user. Opens a rich annotatable document in the user's browser where the user reviews, comments, answers questions, and submits feedback. Supports planning, architecture reviews, code reviews, discovery interviews, implementation summaries, proposals, decision documents, and explanations.
Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. When Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks
This skill should be used when the user asks to "handle copilot review", "run copilot review loop", "fix copilot issues", "process copilot feedback", "resolve copilot comments", "request copilot review", "address copilot review comments", or says "Copilot 又有新的问题" / "帮我处理 Copilot Review" / "跑一下 Copilot Review". Automatically detects the current PR stage (never reviewed, in-progress, has comments, or clean) and runs the full fix-request-wait loop until Copilot raises no new issues.
Use when the user has received review comments on a GitHub PR or GitLab MR and needs to process them — analyze, triage, coordinate fixes, respond, and resolve threads. This is THE skill for any post-review work on a PR/MR. Triggers on: "разберись с комментариями", "address review comments", "handle review feedback", "respond to reviewers", "fix review comments", "deal with PR/MR comments", "reply to review", "resolve review threads", "go through the feedback", "комментарии к PR/MR", "ревьюер оставил комментарии", "пройдись по комментариям", "тредов после ревью", "reviewer left comments", "got a review", "review feedback on my MR/PR", or any mention of processing, triaging, or responding to existing review comments on a pull request or merge request. Do NOT use for writing new reviews, creating PRs, or CI/CD monitoring — those are separate skills. --- # Address Review Feedback An orchestrator skill. Analyzes all review comments, categorizes them, detects cross-diff patterns, presents an action plan for user confirmation, then coordinates fixes, answers, and thread responses. Does NOT implement code changes itself — it produces task descriptions for implementation agents. **Core principle:** Fix what belongs to this PR. Push back when a suggestion is wrong. Never perform agreement — just act and show evidence. --- ## Phase 1: Fetch & Parse ### Platform detection ```bash REMOTE_URL=$(git remote get-url origin) # Contains github.com → GitHub (gh) # Contains gitlab → GitLab (glab) ``` ### Fetch PR/MR metadata and context Fetch both technical metadata and the PR/MR context — description, linked issues, labels, milestone. This context is essential for Phase 2: understanding the intent behind changes lets you judge whether a comment is in scope, whether a suggestion aligns with the goal, and what trade-offs matter. ```bash # GitHub — metadata + context in one call PR_INFO=$(gh pr view --json number,baseRefName,headRefName,title,body,labels,milestone,closingIssuesReferen
Reviews code for quality, style, and potential issues.
Adds comments to a word doc following commenting guidelines. Use when the user asks for comments, reviews, or feedback on Microsoft Word (.docx) documents. Provides helper scripts and instructions for how to read documents, draft thoughtful comments, and add them programmatically.
Reviews code for complexity and naming
Interactive code review with GitHub comment submission using gh CLI
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:
