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Import Skills

Composite Most Downloads Most Likes Most Comments Newest
drguptavivek drguptavivek
from GitHub Docs & Knowledge
  • 📁 references/
  • 📁 scripts/
  • 📄 SKILL.md
knowledge search when

kb-search

Search and retrieve knowledge from agentic_kb knowledge base. Use when the user requests to search the KB, asks "How do I..." questions that should consult the KB, wants to document new knowledge, or at session start to update the KB submodule. Also use when User wants to udpate the knowledge base with new knowledge. Knowledge Capture when you learn new, reusable knowledge during tasks. Supports Typesense (fast full-text search), FAISS (semantic vector search), and ripgrep (exact pattern matching). All KB is Obsidian formatted and can be browsed easily and visually with network maps in Obsidian.

⬇0 ❤7 1 month ago · Uploaded Detail →
masaomi masaomi
from GitHub Tools & Productivity
  • 📄 SKILL.md
knowledge blockchain auditability

kairos-chain

Self-amendment MCP server framework with layered skill architecture and blockchain auditability. Use when the user wants to manage knowledge, evolve skills, track changes with blockchain, audit skill health, promote knowledge between layers, or perform persona assembly for decision support. --- # KairosChain - Self-Amendment MCP Server Framework KairosChain provides a layered skill architecture (L0/L1/L2) where skills can evolve, promote, and audit themselves with blockchain-backed auditability. ## Architecture ### Three-Layer System - **L0 (Constitution/Law)**: Immutable safety rules and meta-governance. Changes require human approval and full blockchain recording. - **L1 (Knowledge)**: Project knowledge in Anthropic skills format. Changes recorded with hash references. - **L2 (Context)**: Temporary session context. Free modification, no blockchain recording. ### Core Capabilities #### Knowledge Management - `knowledge_list` / `knowledge_get` - Browse and read L1 knowledge skills - `knowledge_update` - Create, update, or delete L1 knowledge with blockchain recording - `context_save` - Save temporary L2 context for session work #### Skill Evolution - `skills_evolve` - Propose and apply changes to L0 skill definitions (requires human approval) - `skills_rollback` - Version management with snapshot and rollback capabilities - `skills_promote` - Promote knowledge between layers (L2→L1, L1→L0) with optional Persona Assembly #### Blockchain Auditability - `chain_status` / `chain_verify` - Check and verify blockchain integrity - `chain_history` - View skill transitions, knowledge updates, and state commits - `chain_record` - Record data to the blockchain - `state_commit` - Create snapshots of all layers for auditability #### Health & Safety - `skills_audit` - Audit knowledge health across layers (conflicts, staleness, dangerous patterns) - `tool_guide` - Dynamic tool discovery and workflow recommendations #### Persona Assembly - Multi-perspective decision support using pe

⬇0 ❤7 1 month ago · Uploaded Detail →
Viniciuscarvalho Viniciuscarvalho
from GitHub Tools & Productivity
  • 📁 .claude/
  • 📁 .claude-plugin/
  • 📁 .github/
  • 📄 .gitignore
  • 📄 .mcp.json
  • 📄 CHANGELOG.md
security knowledge docs

maestro

Intelligent skill knowledge gateway. Routes tasks to the right knowledge without loading all skills into context. MUST be consulted before any coding task — call the search_skills MCP tool to retrieve relevant expertise from 100+ indexed skills covering Swift, SwiftUI, concurrency, testing, architecture, performance, and security.

⬇0 ❤6 1 month ago · Uploaded Detail →
keshrath keshrath
from GitHub Docs & Knowledge
  • 📁 scripts/
  • 📄 SKILL.md
knowledge files ingest

knowledge-ingest

Ingest or update a codebase in the agent-knowledge base. First run bootstraps the knowledge base from scratch; subsequent runs are incremental (only changed/new/deleted files reprocessed). Uses tree-sitter for zero-token structural extraction. Trigger on "/knowledge-ingest", "ingest this codebase", "load this into knowledge", "scan this project", "index this repo", "update knowledge", "refresh knowledge", "re-ingest". --- # knowledge-ingest Populate or update agent-knowledge from a codebase. Tree-sitter extracts structure (zero LLM tokens), then the agent distills clusters into knowledge entries + graph edges via existing MCP tools. **First run**: full ingest — scans all files, creates entries from scratch. **Subsequent runs**: incremental — only reprocesses files whose SHA256 changed, adds entries for new files, removes entries for deleted files. The `.knowledge-ingest-cache.json` file in the target directory tracks state between runs. ## When to use - **Onboarding a new project** — bootstrap the knowledge base so future sessions have context - **After a refactor** — re-run to update subsystem boundaries and relationships - **Periodic refresh** — re-run after significant changes to keep knowledge current - **Importing documentation** — PDFs, architecture diagrams, or external URLs ## When NOT to use - Single-file changes — just write a knowledge entry manually - No code changes since last ingest — the cache will skip everything anyway (fast no-op) ## Procedure ### Phase 0 — Validation 1. Confirm the target path exists and is a directory. 2. Detect project name: - Check `package.json` → `name` field - Check `Cargo.toml` → `[package] name` - Check `go.mod` → `module` line - Check `pyproject.toml` → `[project] name` - Fall back to directory basename 3. Check for `.knowledge-ingest-cache.json` in the target directory. If found, load it — this is an incremental run. Report how many files changed since last ingest. ### Phase 1 — Structural Extraction (zero tokens) 4. Loc

⬇0 ❤5 26 days ago · Uploaded Detail →
dkushnikov dkushnikov
from GitHub Content & Multimedia
  • 📄 SKILL.md
knowledge content library

source-add

Add a source to your Mnemon knowledge library — articles, YouTube videos, podcasts, books, ideas. Captures content and generates a structured extract with personal context framing. Use when the user provides a URL to save, says "add source", "capture this", "save this article/video/podcast", or wants to process any content into their knowledge library.

⬇0 ❤5 1 month ago · Uploaded Detail →
noahbfreedman-cloud noahbfreedman-cloud
from GitHub Tools & Productivity
  • 📄 SKILL.md
agent knowledge automation

shelfai

Use this skill when the user wants to manage AI agent knowledge, organize agent configurations, or set up post-session learning systems. Triggers include: organizing agent skills or knowledge into a structured shelf, extracting insights from conversation transcripts, splitting monolithic agent config files into modular pieces, managing memory files, searching indexed knowledge, or diagnosing shelf health. Use ShelfAI whenever a user mentions managing agent context, chunking configs, learning from sessions, compacting memory, or organizing reusable agent knowledge pieces.

⬇0 ❤5 1 month 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