- 📄 SKILL.md
crafters-cli
Manage Crafter Station domains (Spaceship DNS + Vercel), agent infrastructure, and Claude Code configuration via the crafters CLI.
Manage Crafter Station domains (Spaceship DNS + Vercel), agent infrastructure, and Claude Code configuration via the crafters CLI.
Compress and simplify prompts to preserve meaning while reducing use of context
AKTIVIERT SICH AUTOMATISCH bei vagen Auftraegen. LIEBER EINMAL ZU OFT NACHFRAGEN als falsch implementieren. Erkennungsmerkmale (EINES genuegt!): - Auftrag <25 Woerter - Keine konkreten Dateinamen/Pfade - Vage Verben: besser, optimieren, fixen, machen, aendern, verbessern, anpassen, erweitern, refactoren, aufraumen, ueberarbeiten - Unsichere Sprache: irgendwie, vielleicht, mal eben, schnell, einfach, bisschen, koennte, sollte - Fehlende Erfolgskriterien: Kein damit, sodass, weil, um zu - Relative Begriffe ohne Kontext: schneller, besser, schoener, einfacher Output ist STRUKTURIERTES JSON fuer prompt-architect Skill.
Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains.
Search, recover, and analyze AI session histories across Claude Code, AI Studio, and Gemini CLI. Use when user asks to "find that file from last week", "search sessions", "recover context after compaction", "what did the AI do", "export session to markdown", "find corrections", "analyze session quality", "improve CLAUDE.md from past mistakes", or "turn AI mistakes into rules". Contains session search, file recovery, correction detection, self-improvement workflow.
Reference guide covering decision heuristics for building agents on the Claude API, including tool surface design, context management, caching strategies, and composing tool calls
初始化专用技能。仅在用户显式输入 `$bingo-spec-coding-max-skill` 时使用。将项目初始化为 Spec 驱动结构,创建 AGENTS.md、spec 目录及模板,并把 doc 目录下的提示词与示例注入到 spec/prompts 与 spec/usage。支持中文或英文 spec 环境,默认中文。支持 Windows 与 macOS,默认 dry-run,使用 --apply 才落地。
Set up Morph compaction — adds compact instructions to CLAUDE.md and configures API key
Run a pre-wrap external review gate using GitHub Copilot CLI with Claude Opus 4.6 before finalizing substantial implementation work. Use when Codex has produced or updated plans and code and needs an independent pass for blockers, regressions, edge cases, and test gaps. Skip for trivial or purely conversational responses.
Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface.
Run a multi-turn debate with Codex from Claude Code. Use when Claude should hold a structured point-by-point discussion with Codex over multiple rounds and then synthesize the outcome for the user.
Generate AI images locally using the mold CLI. Use when asked to generate, create, or produce images from text prompts, transform existing images (img2img), or manage local AI models.
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: