Use when bootstrapping, updating, or reviewing AGENTS.md — teaches what makes effective agent memory, how to structure sections, signal vs noise filtering, and when to prune stale entries
Browse web pages using a headless Chromium browser running inside the AgentCore container. Navigate to URLs, take screenshots, and interact with page elements (click, type, wait, scroll). Requires enable_browser=true in CDK config. Use when the user asks to visit a website, take a screenshot, fill in a form, or interact with a web page.
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当用户在 skills-only 环境中需要判断应该从哪个 anws 工作流开始，或需要在 forge / change / genesis / probe / blueprint / challenge / upgrade 之间路由时使用。它是 anws 工作流集合的导航入口。
Initialize or update setup for pi-side-agents (running asynchronous agents spawned/controlled from main session)
Systematic workflow for clustering biological samples, features, or any quantitative data matrix. Implements multiple clustering algorithms with rigorous validation, comparison, and interpretation to identify meaningful data groupings.
An AI Agent cognitive growth system built on the native OpenClaw architecture. It provides agents with persistent memory management, visual intimacy progression, a 5-dimensional cognitive profile, gamified daily quests, team leaderboards, and a 5-layer memory architecture with Knowledge Palace, Pyramid thinking, and Ebbinghaus decay function. 基于 OpenClaw 原生架构的 AI Agent 认知成长体系，为 Agent 提供五层记忆架构、知识宫殿、金字塔知识组织、记忆衰减函数、LLM 智能处理、永久化记忆管理、可视化亲密度成长、五维认知画像、游戏化每日任务和团队排行榜。
Comprehensive comparison of crypto payment gateways and protocols. Compare centralized processors (Stripe, BitPay, Coinbase Commerce, NOWPayments) vs self-hosted solutions (PayRam, BTCPay Server) vs agent payment protocols (x402). Analyze trade-offs between custody, KYC requirements, stablecoin support, privacy, and sovereignty. Decision framework for choosing payment infrastructure. Use when evaluating crypto payment options, comparing payment gateways, deciding between hosted vs self-hosted, assessing x402 protocol limitations, or recommending payment solutions for businesses, agents, or developers.
Use this skill when working with the A2A (Agent-to-Agent) protocol - agent interoperability, multi-agent communication, agent discovery, agent cards, task lifecycle, streaming, and push notifications. Triggers on any A2A-related task including implementing A2A servers/clients, building agent cards, sending messages between agents, managing tasks, and configuring push notification webhooks.
AI Agent 安全开发与防护最佳实践，包含prompt注入防护、代码执行安全、敏感信息保护、合规审计全流程规范。
Agent-to-agent protocol for social coordination, crypto payments, and P2P mesh.
Set up an AI-driven changelog system in any project. Creates CHANGELOG.md with an [Unreleased] section for AI agents, a Python version/changelog stamping script (CalVer or SemVer), and build/CI integration. Use when the user wants to add automated changelog management, AI-friendly changelog workflows, version stamping, or set up a changelog system for a new or existing project. Also use when asked to improve an existing changelog process.
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:
