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♾️ Free & Open Source 🛡️ Secure & Worry-Free

Import Skills

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opensearch-project opensearch-project
from GitHub Data & AI
  • 📁 references/
  • 📁 scripts/
  • 📄 SKILL.md
search data log

opensearch-launchpad

Build search applications and query log analytics data with OpenSearch. Use this skill when the user mentions OpenSearch, search app, index setup, search architecture, semantic search, vector search, hybrid search, BM25, dense vector, sparse vector, agentic search, RAG, embeddings, KNN, PDF ingestion, document processing, or any related search topic. Also use for log analytics and observability — when the user wants to set up log ingestion, query logs with PPL, analyze error patterns, set up index lifecycle policies, investigate traces, or check stack health. Activate even if the user says log analysis, Fluent Bit, Fluentd, Logstash, syslog, traceId, OpenTelemetry, or log analytics without mentioning OpenSearch.

⬇0 ❤6 23 days ago · Uploaded Detail →
benoitvx benoitvx
from GitHub Data & AI
  • 📄 SKILL.md
data api data.gouv.fr

datagouv-apis

Interact with data.gouv.fr APIs — Main API (datasets, orgs, users, resources, reuses, discussions), Metrics API (usage/stats by model), Tabular API (query CSV rows by resource ID). Use when working with data.gouv.fr data, catalog, or platform features.

⬇0 ❤6 23 days ago · Uploaded Detail →
olaservo olaservo
from GitHub Data & AI
  • 📄 implementation.ts
  • 📄 SKILL.md
issues data recommendations

comprehensive-issue-analyzer

Fetches ALL open issues from any GitHub repository using pagination and generates a comprehensive analysis including category breakdown, age distribution, stale issues (30+ days), top discussed issues, prioritization, and detailed recommendations for triage. Handles large repositories (5000+ issues) efficiently.

⬇0 ❤6 24 days ago · Uploaded Detail →
NominexHQ NominexHQ
from GitHub Data & AI
  • 📄 SKILL.md
memory heatmap ascii

pmm-dump

Dump PMM memory state as ASCII art in the terminal. Three depth levels: status (heatmap only), summary (heatmap + clusters + timeline), detailed (full ASCII). Runs as a subagent. Use when the user runs /pmm-dump or asks for a text-based memory overview. Trigger on: "pmm-dump", "/pmm-dump", "dump memory", "ascii memory", "text memory overview", "show memory heatmap", "memory dump", or any request for a text-based ASCII visualization of memory state. --- # PMM Dump Render PMM memory state as inline ASCII visualizations. Runs as a subagent to keep the main context clean. **Depth level:** $ARGUMENTS (default: `status` if empty or not provided) ## Invocation - `/pmm-dump` or `/pmm-dump status` — heatmap only (status level) - `/pmm-dump summary` — heatmap + cluster list + last 5 timeline entries - `/pmm-dump detailed` — full ASCII: graph map + heatmap + similarity matrix + clusters ## Behaviour Dispatch a `general-purpose` agent using the `Readonly Agent Model` from `memory/config.md` (default: `haiku`) with the prompt below. Replace `<level>` with the depth level (`status`, `summary`, or `detailed`). Replace `<project-root>` with the actual project root path. Output the agent's returned string verbatim — it contains the fully formatted ASCII visualization. ### Agent Prompt > Render PMM memory state as ASCII visualizations. This is a READ-ONLY task — do not edit any files. You may run git commands for timestamps. > > **Project root:** `<project-root>` > **Depth level:** `<level>` > > ### Depth Levels > > - `status` — Heatmap only > - `summary` — Heatmap + cluster list + last 5 timeline entries > - `detailed` — Full ASCII: graph map + heatmap + similarity matrix + clusters > > ### Visualization 1: Heatmap — File Activity (all levels) > > 1. Read `<project-root>/memory/config.md` to get the list of active files > 2. For each active file, run: `git log -1 --format="%ar|%at" -- memory/<filename>` > 3. Map the unix timestamp to a heat level: > - `████` = modified < 5 minute

⬇0 ❤6 24 days ago · Uploaded Detail →
NYBaywatch NYBaywatch
from GitHub Data & AI
  • 📄 SKILL.md
detection network service

agrus-scanner

Network reconnaissance and AI/ML service detection. Scan IP ranges with ping sweeps, port scanning, DNS resolution, and AI service probing across 45 detection signatures. Use when the user wants to discover hosts, open ports, or AI/ML services on a network.

⬇0 ❤6 25 days ago · Uploaded Detail →
utensils utensils
from GitHub Data & AI
  • 📄 SKILL.md
images ai generate

mold

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.

⬇0 ❤6 25 days ago · Uploaded Detail →
owen-ever owen-ever
from GitHub Data & AI
  • 📁 references/
  • 📄 SKILL.md
zigrix work plain-language

oz

Official OpenClaw Zigrix entrypoint. Force Zigrix delegation when a message starts with `/oz`, and semantically route plain-language requests to hand work off, assign it, or have Zigrix take it instead of doing the work directly.

⬇0 ❤5 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