Create and configure AI Configs in LaunchDarkly. Helps you choose between agent vs completion mode, create the config, add variations with models and prompts, and verify the setup.
Send tasks to Claude Code instances on remote machines. Enables Claude-to-Claude collaboration over SSH with session continuity.
· Build, review, or architect AI/ML applications -- LLM integrations, RAG pipelines, agent systems, embeddings, evals, local inference, structured output, and tool use. Triggers: 'llm', 'rag', 'embedding', 'vector store', 'langchain', 'openai sdk', 'anthropic sdk', 'agent loop', 'fine-tune', 'ollama', 'vllm', 'evals', 'guardrails', 'chunking', 'reranking'. Not for MCP servers (use mcp), prompt writing (use prompt-generator), or general DB (use databases).
AEO (Answer Engine Optimization / AI Visibility) audit skill. Checks 4 categories: AI bot access (robots.txt, GPTBot, ClaudeBot), structured data (Schema.org/JSON-LD), content structure, and technical factors (HTTPS, sitemap, llms.txt). Scores 0-100 with ROI-ranked recommendations and generates a print-ready HTML/PDF report.
Use when a user wants to customize a Claude Code buddy, change only the companion soul, or search for a UUID seed that rerolls buddy attributes before updating Claude settings
Use the t2i CLI to generate AI images from text prompts via Microsoft Foundry providers (FLUX.2, MAI-Image-2). Activate when the user asks to generate images, automate image creation in scripts, or set up image generation for CI/CD.
Watch a tutorial or demo video and generate a Claude Code skill from it. Activated when user says "create a skill from this video" or similar.
Design a real harness for an agentic system using Claude Code-inspired patterns. Use when the user needs a harness blueprint, request assembly design, execution loop, tool runtime, memory layering, permission model, transcript or recovery strategy, or wants to turn a vague agent idea into a harness-level architecture. Do not use for generic product brainstorming, simple prompt writing, or isolated code generation.
This skill should be used when the user asks to "create a plugin", "scaffold a plugin", "understand plugin structure", "organize plugin components", "set up plugin.json", "use ${CLAUDE_PLUGIN_ROOT}", "add commands/agents/skills/hooks", "configure auto-discovery", or needs guidance on plugin directory layout, manifest configuration, component organization, file naming conventions, or Claude Code plugin architecture best practices.
Use when: creating, refactoring, auditing, upgrading, or debugging Copilot custom agents, skills, instructions, prompts, or hooks for Apple platform software engineering and agile delivery workflows.
PR 변경 내용을 분석하여 .claude/context/ 문서를 자동 생성하는 규칙
Use when converting a research paper into teaching-oriented lecture material or a NotebookLM Custom Presentations prompt, especially when you need a short high-signal prompt rather than a long summary-style instruction block.
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:
