Synchronize LocalMultiControl progress to Feishu Bitable task boards by upserting records after code or docs work. Use when users ask to update Feishu multi-dimensional tables, sync task status, backfill historical tasks from commits/docs, or keep player-visible progress boards current.
Bootstrap a knowledge store by exploring codebase architecture — use when starting with a new or empty project, seeding knowledge, or running /bootstrap
Design, review, simplify, restructure, or standardize project documentation, especially for open-source or developer-facing repos where the goal is better information architecture, less duplication, faster onboarding, and ultra-compact contributor docs. It is especially appropriate when the request is about best practices, document responsibilities, ToC design, doc boundaries, contributor experience, or AI-assisted documentation workflows rather than writing detailed technical content itself.
Use when user wants to align docs with the current project status or new discoveries
Scan codebase and fill/update CLAUDE.md and AGENTS.md with real project data. Produces deep architectural documentation matching production quality.
Converts content to clean markdown. Supports web pages, Google Docs, PDFs, images, videos, audio files, YouTube videos, Word docs, EPUBs, CSVs, PowerPoints, tweets, and RSS feeds. Use when the user wants to convert a URL or file to markdown, extract text from a PDF or image, transcribe a video or audio file, save a web article, export a Google Doc, or get a YouTube transcript.
Use when user says 'superflow', 'суперфлоу', or asks for full dev workflow. Four phases: (0) project onboarding & CLAUDE.md bootstrap, (1) collaborative Product Discovery with multi-expert brainstorming, (2) fully autonomous execution with PR-per-sprint, git worktrees, dual-model reviews, max parallelism, and verification discipline, (3) merge with documentation update.
Use this skill when answering software questions where documentation currency
Audit an existing repository or paper-code release for open-source hardening gaps across correctness, maintainability, testability, security, performance, observability, and documentation. Use when the user says "audit this repo", "harden this project", "open source readiness", or wants a prioritized file-level report before changing code.
Turns X/Twitter bookmarks into a searchable, proactive personal knowledge base for AI agents.
RESTful API design patterns, HTTP standards, versioning, error handling, and documentation
Perform a structured codebase health assessment and append results to docs/health-log.md. Use when asked to check codebase health.
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:
