Register this AI agent on-chain via ERC-8004 Identity Registry on Base, link to the Augmi marketplace, check reputation. Use this skill when setting up a new agent or checking registration status.
This skill should be used when the user asks to "configure agents", "create a custom agent", "set up agent permissions", "customize agent behavior", "switch agents", or needs guidance on OpenCode agent system.
Production-grade Agent development methodology extracted from Claude Code. 7-dimension framework covering tool design, system prompts, permission & safety, multi-agent orchestration, token economy, memory/state, and extensibility. Supports architecture design, implementation guidance, and agent review. Trigger on "Agent design", "build an agent", "AI agent", "tool design", "system prompt architecture", "agent review", "multi-agent", or any agent development concern.
Build AI agents using ya-agent-sdk with Pydantic AI. Covers agent creation via create_agent(), toolset configuration, session persistence with ResumableState, subagent hierarchies, and browser automation. Use when creating agent applications, configuring custom tools, managing multi-turn sessions, setting up hierarchical agents, or implementing HITL approval flows.
Protect .env secrets from AI agents. Real credentials encrypted in a vault — agents see structurally valid sandbox values on disk.
Set up evals for an agent codebase or check eval status after changes. Determines readiness, identifies what can be tested, and prepares the environment. Use when starting evals for the first time, returning after a code change, or figuring out what to do next. Also triggered by "set up evals", "is my agent ready?", "eval status", "what should I do next?", "init eval", "evaluate my agent", "test my agent", "help me eval this", "get started with evals", "where do I start", "how do I test this agent", "check my setup". This is the default entry point, use it whenever a user wants to evaluate an agent and you're unsure which skill to start with.
Trust and reputation enforcement for AI agent interactions using Agent Veil Protocol. Check peer reputation before delegating tasks, submit attestations after interactions, discover agents by capability, and verify audit trails. Works through the AVP MCP server which provides 11 tools for identity, reputation, attestations, and discovery. Use when interacting with other AI agents, delegating work, evaluating task results, or when the user mentions trust, reputation, agent verification, or Agent Veil.
通用开发任务编排器。将复杂开发任务拆解为专业 agent 角色并协调协作。当需要'组建团队'、'任务分解'、'多 agent 协作'、'组队开发'、'并行开发'、'团队协作'时使用。后续任务支持：'修改团队'、'调整分工'、'重新执行'、'更新计划'、'仅重新执行某阶段'。对于简单任务或单文件改动，直接完成，仅在复杂度确实需要多角色协作时启用。
Connect your OpenClaw agent to the EvoMate Evolution Lab. Create or join a private evolution room using a Room Code, then breed a next-generation child agent through real-time genetic fusion with a partner agent.
Use when the user asks about Agent SDK permissions, canUseTool callback, permission modes, hooks system, PreToolUse/PostToolUse, custom subagents, agent definitions, structured output, outputFormat, sandbox configuration, budget controls, maxTurns, file checkpointing, or thinking/effort configuration.
Hardware-secured Solana wallet, trading terminal, and agent identity layer. Trade on Jupiter DEX, earn DeFi yield, snipe meme coins with rug-pull detection, build trading bots — plus agent identity, encrypted agent-to-agent messaging, and service discovery for autonomous agent commerce. All signed by Apple Secure Enclave (no .env private keys). TRIGGER when: user mentions Solana, SOL, USDC, SPL tokens, Jupiter, Raydium, swap, DEX, meme coin, token price, DeFi yield, lending, on-chain balance, crypto wallet, send crypto, pay crypto, sign message, agent identity, agent messaging, agent commerce, agent discovery, copy trading, whale tracking, trading bot, or any Solana token symbol/mint address. Also trigger when: user asks to check a token, buy/sell tokens, transfer funds on Solana, earn yield, or interact with other AI agents economically.
Review Agent Skill directories and SKILL.md files against best practices. Use this skill when the user wants to review, validate, or check an Agent Skill implementation.
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:
