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Import Skills

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avivsinai avivsinai
from GitHub Data & AI
  • 📁 references/
  • 📄 SKILL.md
data langfuse ai

langfuse

Debug AI traces, find exceptions, analyze sessions, and manage prompts via Langfuse MCP. Use when debugging AI pipelines, investigating errors, analyzing latency, managing prompt versions, or setting up Langfuse. Triggers on "langfuse", "traces", "debug AI", "find exceptions", "what went wrong", "why is it slow", "datasets", "evaluation sets".

⬇0 ❤73 27 days ago · Uploaded Detail →
AltimateAI AltimateAI
from GitHub Data & AI
  • 📄 SKILL.md
models dbt sql

creating-dbt-models

Creates dbt models following project conventions. Use when working with dbt models for: (1) Creating new models (any layer - discovers project's naming conventions first) (2) Task mentions "create", "build", "add", "write", "new", or "implement" with model, table, or SQL (3) Modifying existing model logic, columns, joins, or transformations (4) Implementing a model from schema.yml specs or expected output requirements Discovers project conventions before writing. Runs dbt build (not just compile) to verify. --- # dbt Model Development **Read before you write. Build after you write. Verify your output.** ## Critical Rules 1. **ALWAYS run `dbt build`** after creating/modifying models - compile is NOT enough 2. **ALWAYS verify output** after build using `dbt show` - don't assume success 3. **If build fails 3+ times**, stop and reassess your entire approach ## Workflow ### 1. Understand the Task Requirements - What columns are needed? List them explicitly. - What is the grain of the table (one row per what)? - What calculations or aggregations are required? ### 2. Discover Project Conventions ```bash cat dbt_project.yml find models/ -name "*.sql" | head -20 ``` Read 2-3 existing models to learn naming, config, and SQL patterns. ### 3. Find Similar Models ```bash # Find models with similar purpose find models/ -name "*agg*.sql" -o -name "*fct_*.sql" | head -5 ```

⬇0 ❤73 27 days ago · Uploaded Detail →
borghei borghei
from GitHub Data & AI
  • 📁 scripts/
  • 📄 SKILL.md
churn architecture campaigns

churn-prevention

SaaS churn reduction covering cancel flow design, dynamic save offers, exit survey architecture, dunning sequences, payment recovery, win-back campaigns, and churn impact modeling.

⬇0 ❤72 26 days ago · Uploaded Detail →
ClariSortAi ClariSortAi
from GitHub Ops & Delivery
  • 📁 references/
  • 📄 SKILL.md
devops plan interactive

onboarding

This skill should be used when the user asks to "set up OpenClaw", "get started", "onboard me", "plan my setup", or "help me choose channels". Conducts an interactive interview, then generates a tailored deployment plan.

⬇0 ❤72 26 days ago · Uploaded Detail →
gainubi gainubi
from GitHub Research & Analysis
  • 📁 agents/
  • 📁 references/
  • 📄 SKILL.md
word 任务书或示例论文 再对本科或硕士毕

thesis-word-formatter

大学生毕业论文 Word 排版技能。用于先收集学校 Word 模板、学院规范、任务书或示例论文，再对本科或硕士毕业论文进行 Word 版式整理、目录与编号校正、参考文献与图表题注检查，并输出可直接复核的排版执行清单。适用于用户说“给毕业论文排版”“按学校要求整理 Word”“检查论文格式”“论文目录标题编号不对”“把这篇论文整理成提交版”等场景。

⬇0 ❤71 23 days ago · Uploaded Detail →
AllBeingsFuture AllBeingsFuture
from GitHub Development & Coding
  • 📁 templates/
  • 📄 LICENSE.txt
  • 📄 SKILL.md
art algorithmic creating

allbeingsfuture/skills@algorithmic-art

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

⬇0 ❤72 27 days ago · Uploaded Detail →

Skill File Structure Sample (Reference)

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

SKILL.md Requirements

├─ ⭐ 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

Why SkillWink?

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.

Keyword Search Version Updates Multi-Metric Ranking Open Standard Discussion

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.

FAQ

Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.

1. What are Agent Skills?

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.

2. How do Skills work?

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.

3. How can I quickly find the right skill?

Use these three together:

  • Semantic search: describe your goal in natural language.
  • Multi-filtering: category/tag/author/language/license.
  • Sort by downloads/likes/comments/updated to find higher-quality skills.

4. Which import methods are supported?

  • Upload archive: .zip / .skill (recommended)
  • Upload skills folder
  • Import from GitHub repository

Note: file size for all methods should be within 10MB.

5. How to use in Claude / Codex?

Typical paths (may vary by local setup):

  • Claude Code：~/.claude/skills/
  • Codex CLI：~/.codex/skills/

One SKILL.md can usually be reused across tools.

6. Can one skill be shared 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.

7. Are these skills safe to use?

Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.

8. Why does it not work after import?

Most common reasons:

  • Wrong folder path or nested one level too deep
  • Invalid/incomplete SKILL.md fields or format
  • Dependencies missing (Python/Node/CLI)
  • Tool has not reloaded skills yet

9. Does SkillWink include duplicates/low-quality skills?

We try to avoid that. Use ranking + comments to surface better skills:

  • Duplicate skills: compare differences (speed/stability/focus)
  • Low quality skills: regularly cleaned up