Daily Featured Skills Count
3,626 3,840 3,909 3,920 3,927 3,966 4,007
04/05 04/06 04/07 04/08 04/09 04/10 04/11
♾️ Free & Open Source 🛡️ Secure & Worry-Free

Import Skills

Composite Most Downloads Most Likes Most Comments Newest
amplitude amplitude
from GitHub Tools & Productivity
  • 📁 references/
  • 📁 scripts/
  • 📄 SKILL.md
run automation cursor

event-description-generator

Orchestrate event description audits by delegating chunk work to the event-descriptions-worker subagent. Resolve a project name to projectId via get_context when needed, then spawn worker subagents over cursors for a bounded run window and write outputs into run-scoped directories. Use when auditing missing event descriptions at scale without doing per-event analysis directly in this skill. --- # Event Description Generator Run this skill as an **orchestrator only**. Do not perform per-event filtering, repo search, or description-writing logic in this skill body. Delegate chunk processing to the `event-descriptions-worker` subagent. ## Workflow 1. Resolve project input (`projectId` or project name) 2. Create a run ID with short git SHA (`<projectId>-<sha>`) 3. Create run directories under `runs/` 4. Determine cursor plan (`cursorStart`, `maxEvents`, chunk size) 5. Spawn `event-descriptions-worker` subagents for cursor chunks 6. Collect worker summaries + output paths 7. Compress the run into a single CSV 8. Report concise progress and next cursor ## Execution Rules - Keep this skill as a **dispatcher**; the worker does the heavy lifting. - Do not call `set_event_metadata` from this skill. - Do not manually re-implement worker filtering/search logic here. - Preserve user control over scope (project, cursor range, chunk size, parallelism). ## Prerequisites

⬇0 ❤18 9 days ago · Uploaded Detail →
docxology docxology
from GitHub Tools & Productivity
  • 📁 config/
  • 📁 core/
  • 📁 docker/
  • 📄 __init__.py
  • 📄 AGENTS.md
  • 📄 PAI.md
infrastructure automation cursor

infrastructure-overview

Top-level skill for the research template infrastructure layer. Use in Cursor, Claude Code, or similar agents when editing or importing anything under infrastructure/, understanding the two-layer architecture, or wiring build/validation/rendering/publishing. Covers module discovery, import patterns, thin orchestrators, per-subpackage SKILL.md paths, and .cursor/skill_manifest.json (see infrastructure.skills).

⬇0 ❤13 10 days ago · Uploaded Detail →
ast-ashulga ast-ashulga
from GitHub Tools & Productivity
  • 📄 SKILL.md
cursor automation agents

c2c

Migrate Claude Code .claude/ configurations to Cursor IDE — skills → .cursor/skills/, agents → .cursor/agents/, rules → .cursor/rules/*.mdc, with semantic fidelity per source type

⬇0 ❤6 12 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