eip
Analyze Ethereum Improvement Proposals by fetching content and optionally deep-diving into implementations
Free to get · One-click to use
Analyze Ethereum Improvement Proposals by fetching content and optionally deep-diving into implementations
Self-improving skills toolkit that watches real agent sessions, detects missed triggers, grades execution quality, and evolves skill descriptions to match how users actually talk. Use when grading sessions, generating evals, evolving skill descriptions or routing tables, checking skill health, viewing the dashboard, ingesting sessions from other platforms, or running autonomous improvement loops. Make sure to use this skill whenever the user mentions skill improvement, skill performance, skill triggers, skill evolution, skill health, undertriggering, overtriggering, session grading, or wants to know how their skills are doing — even if they don't say "selftune" explicitly.
Use for any code change — bug fix, small feature, refactor, or improvement. Ensures TDD, clarifying questions, codebase investigation, DRY, proper branching/worktrees, UI skills, and doc updates. PDD invokes this automatically for large features.
深度阅读和理解源代码。触发场景: - "解释这个文件/模块是做什么的" / "这段代码干什么用的" - "梳理这个项目的架构" / "帮我看懂这个项目" - "追踪 [函数名] 的执行流程" / "[函数] 是怎么工作的" - "这段代码的核心逻辑是什么" / "帮我理解这段代码" - "帮我理解 [特定功能] 是如何实现的" / "这个功能怎么实现的" - "这个 [类/接口/类型] 是怎么用的" - "为什么这里要这么写" / "这个设计是什么意图" - "这个项目可以有哪些改进" / "有什么可以优化的" - "这部分代码可以怎么改" / "给我列出修改建议" - "这个模块可以增加什么功能" / "可以添加什么特性" - "帮我看看哪些地方需要改进" / "有什么 improvement" - "/code-explorer [路径或函数名]"
Lean manufacturing (Jidoka + JIT) based anomaly detection, root cause analysis, and continuous improvement skill
Review a source file for code quality, potential issues, and improvement suggestions.
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: