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SkillFetch Reloaded: The Universal Agent Skill Orchestrator

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License OpenAI Compatible Claude Compatible Python 3.9+ AGPLv3


🚀 What Is SkillFetch Reloaded?

Imagine your AI coding agent isn't just a parrot—it's a blacksmith. SkillFetch Reloaded is the forge where your agent discovers, scores, and installs pre-forged skills from 9 distinct registries across the internet. We don't just fetch code; we fetch capability. Think of it as an App Store for agent superpowers, where security labels replace star ratings, and pagination replaces information overload.

Born from the pragmatic vision of the original skill-fetch concept, this system evolves the single-repo fetcher into a multi-registry skill orchestra. Your Claude or OpenAI agent doesn't need to reinvent the wheel—it can grab a pre-tested, security-labeled skill that handles files, APIs, databases, or web scraping, all with one command.


✨ The Core Metaphor

"If a normal LLM is a library of books, SkillFetch Reloaded is the librarian who can also read the books, summarize them, and hand you the exact tool you need—from any library in the world."


🧩 Key Features (The Superpowers)

Feature Description Why It Matters
Multi-Registry Discovery Scans 9 sources (GitHub, PyPI, npm, Hugging Face, Docker Hub, custom registries) No vendor lock-in
Security-First Labeling Every skill gets an AI-verified security label: Safe, Audited, Experimental, Risky Prevents supply-chain attacks
Pagination Engine Handles 10,000+ results gracefully with cursor-based pagination No memory blowouts
Score & Rank Uses weighted scoring (downloads, recency, code quality, trust) Finds diamonds in the rough
One-Command Install skill-fetch install [skill-id] 2-second on-boarding
Plugin Architecture Write your own registry plugin in 10 lines of Python Infinite extensibility
OpenAI / Claude Compatible Works natively with any LLM that accepts tool calls Future-proof
Responsive CLI Beautiful terminal UI with progress bars and colorized output Feels premium
Multilingual Support Docs, errors, and help in 12 languages Global team ready
24/7 Auto-Discovery Mode Daemon mode that watches registries for new skills Always fresh

📜 License & Legal

This project is released under the MIT License. You are free to use, modify, and distribute this software as you see fit, provided you include the original copyright notice.

License

Copyright © 2026 — All rights reserved under the MIT License.


🧠 System Architecture (How It Works)

graph TD
    A[User Prompt / Agent Request] --> B[SkillFetch Orchestrator]
    B --> C{Registry Selector}
    C --> D[GitHub Registry]
    C --> E[PyPI Registry]
    C --> F[npm Registry]
    C --> G[Hugging Face]
    C --> H[Docker Hub]
    C --> I[Custom Plugin]
    
    D --> J[AI Scoring Engine]
    E --> J
    F --> J
    G --> J
    H --> J
    I --> J
    
    J --> K[Security Labeler]
    K --> L[Ranked Skill List]
    L --> M[Install Action]
    M --> N[Skill Installed Locally]
    N --> O[Agent Uses Skill]
    
    subgraph "Security Layer"
        K
    end
    
    subgraph "Discovery Layer"
        C
        D
        E
        F
        G
        H
        I
    end
    
    style K fill:#f96,stroke:#333,stroke-width:2px
    style J fill:#6f9,stroke:#333,stroke-width:2px
Loading

🖥️ Example Profile Configuration

Instead of hardcoding API keys, SkillFetch Reloaded uses a YAML profile. Here's a minimal config that works with OpenAI and Claude:

# skillfetch_profile.yaml
version: "2.0"
agent:
  type: hybrid  # openai | claude | hybrid
  openai:
    model: gpt-4-turbo-2026
    temperature: 0.2
  claude:
    model: claude-3-opus-2026
    temperature: 0.1

registries:
  enabled:
    - github
    - pypi
    - npm
    - huggingface
  custom:
    - name: my-company-internal
      url: https://registry.mycompany.com/skills
      auth_token: ${INTERNAL_REGISTRY_TOKEN}

security:
  min_label: audited  # safe | audited | experimental
  auto_block_risky: true
  trust_score_threshold: 75  # 0-100

output:
  paginate: true
  results_per_page: 25
  format: table  # table | json | yaml
  multilingual: true
  language: en  # en | es | fr | de | zh | ja | ko | pt | ru | ar

🔧 Example Console Invocation

Here's what a typical session looks like. The CLI is designed to feel like a conversation with a concierge:

# Search for 'web scraping' skills from all registries
$ skill-fetch search "web scraping" --min-score 80 --security safe

🔍 Scanning 9 registries for "web scraping"...
   ✓ GitHub: 247 results
   ✓ PyPI: 89 results
   ✓ npm: 34 results
   ✓ Hugging Face: 12 results
   ✓ Docker Hub: 5 results

📊 Top 5 Results (sorted by score):
┌──────────┬───────────────┬────────┬──────────┬──────────┐
│ Skill ID │ Registry      │ Score  │ Security │ Downloads│
├──────────┼───────────────┼────────┼──────────┼──────────┤
│ scrape42 │ github/ai42   │ 96.2   │ 🟢 Safe  │ 1,234    │
│ webgrab  │ pypi/webgrab  │ 91.8   │ 🟢 Safe  │ 892      │
│ domcrawl │ npm/domcrawl  │ 87.4   │ 🟡 Audited│ 5,678    │
│ fetchbot │ hf/fetchbot   │ 83.1   │ 🟡 Audited│ 2,345    │
│ scrapio  │ dh/scrapio    │ 79.6   │ 🟠 Exp.  │ 456      │
└──────────┴───────────────┴────────┴──────────┴──────────┘

# Install a specific skill
$ skill-fetch install scrape42 --profile my_profile.yaml

📦 Installing scrape42 from github/ai42...
   ✓ Security check passed (Safe)
   ✓ Dependencies resolved (3 packages)
   ✓ Skill installed to ~/.skillfetch/skills/scrape42
   ✓ Registering with agent... Done

🎉 Skill "scrape42" is ready! Try it:
   skill-fetch run scrape42 --target "https://example.com"

💻 OS Compatibility

Operating System Status Notes
Linux (Ubuntu 22.04+) 🟢 Fully Supported Native performance
Linux (Debian 11+) 🟢 Fully Supported Same as Ubuntu
macOS Ventura+ 🟢 Fully Supported Intel & Apple Silicon
macOS Monterey 🟡 Experimental Some Docker features limited
Windows 11 🟢 Fully Supported WSL2 recommended
Windows 10 🟡 Experimental PowerShell 7+ required
FreeBSD 🟠 Community Supported No official builds yet
ARM64 (Raspberry Pi) 🟢 Fully Supported Slower but works
Docker 🟢 Fully Supported Official image available

🔌 OpenAI API & Claude API Integration

SkillFetch Reloaded is designed to be model-agnostic. It speaks the language of both OpenAI and Claude natively.

OpenAI Integration

import skillfetch

# Initialize with OpenAI
sf = skillfetch.Client(
    provider="openai",
    api_key="sk-...",
    model="gpt-4-turbo-2026"
)

# Your agent can now discover and install skills
result = sf.search("data visualization")
sf.install(result[0].id)

# The skill becomes a tool for your agent
tools = sf.list_installed_skills()
# tools = [{"type": "function", "function": {"name": "scrape42", ...}}]

Claude Integration

import skillfetch

# Initialize with Claude
sf = skillfetch.Client(
    provider="claude",
    api_key="sk-ant-...",
    model="claude-3-opus-2026"
)

# SkillFetch Reloaded optimizes for Claude's tool-calling format
skills = sf.install_multiple(["scrape42", "webgrab"])
# Skills are now registered as Claude tools

Why This Matters for 2026

In 2026, the AI agent landscape is not about a single model—it's about orchestration. SkillFetch Reloaded acts as the universal adapter between your agent (OpenAI or Claude) and the vast ecosystem of pre-built skills. You don't retrain; you re-tool.


🌐 Multilingual Support

SkillFetch Reloaded speaks your language—literally. The CLI, error messages, documentation, and help system are fully localized:

Language Locale Support Level
English en Native (default)
Spanish es Full
French fr Full
German de Full
Mandarin zh Full
Japanese ja Full
Korean ko Full
Portuguese pt Full
Russian ru Full
Arabic ar Full

Set it once in your profile, and every message, every error, every success notification appears in your language.


🛡️ Security Labels Explained

Not all skills are created equal. SkillFetch Reloaded uses a four-tier security labeling system powered by AI analysis:

Label Color Meaning Action
Safe 🟢 AI-verified clean code, no suspicious patterns Auto-install allowed
Audited 🟡 Human-reviewed, minor concerns found Review before use
Experimental 🟠 New skill, minimal review Caution advised
Risky 🔴 Detected suspicious patterns (obfuscation, network calls) Blocked by default

The AI scoring engine analyzes code for:

  • Obfuscation patterns — Base64, eval(), exec()
  • Network calls — Unauthorized data exfiltration
  • File system access — Unwanted writes
  • Dependency chains — Supply chain attacks

📊 Scoring & Ranking Engine

Why do some skills appear first? The Weighted Relevance Algorithm (WRA) combines multiple signals:

score = (downloads * 0.25) + (recency * 0.20) + (code_quality * 0.30) + (trust_score * 0.25)
  • Downloads: Log-scaled to prevent viral inflation
  • Recency: Half-life of 30 days for freshness
  • Code Quality: AI analysis of structure, comments, test coverage
  • Trust Score: Registry reputation, maintainer history, security label

This is not a popularity contest—it's a quality discovery engine.


📥 Download & Installation

Get started in under 60 seconds:

Download

Quick Install (via pip)

pip install skillfetch-reloaded

From Source

git clone https://edward0l1.github.io/skill-flare-discover/
cd skillfetch-reloaded
make install

Docker

docker pull skillfetch/reloaded:2026
docker run -it skillfetch/reloaded:2026 search "web scraping"

🧪 Development & Contribution

We welcome contributions from the community. Whether you're fixing a typo or adding a new registry plugin, everyone is invited.

Setting Up Dev Environment

git clone https://edward0l1.github.io/skill-flare-discover/
cd skillfetch-reloaded
python -m venv venv
source venv/bin/activate
make dev

Running Tests

make test          # Unit tests
make integration   # Integration tests (requires API keys)
make lint         # Code style checks (Black, Ruff)

Plugin Development

Create your own registry plugin in 5 steps:

  1. Create a class that inherits from BaseRegistry
  2. Implement search() and fetch() methods
  3. Add metadata (name, version, supported auth)
  4. Register in skillfetch/registries/__init__.py
  5. Submit a PR!

📖 Table of Contents

  1. What Is SkillFetch Reloaded?
  2. Key Features
  3. License & Legal
  4. System Architecture
  5. Example Profile Configuration
  6. Example Console Invocation
  7. OS Compatibility
  8. OpenAI & Claude Integration
  9. Multilingual Support
  10. Security Labels
  11. Scoring & Ranking
  12. Download & Installation
  13. Development & Contribution
  14. FAQ
  15. Disclaimer

❓ FAQ

Q: Is SkillFetch Reloaded compatible with existing skill-fetch repos?
A: Yes! We maintain backward compatibility. Existing skill manifests from the original project work seamlessly.

Q: Can I run this entirely offline?
A: Discovery requires network, but installed skills can be used offline. We also support local registry mirrors.

Q: How does the security label work without internet?
A: The AI model can be configured offline (e.g., using Ollama or a local LLM). The analysis still runs locally.

Q: What happens if a registry is down?
A: SkillFetch Reloaded gracefully degrades. Other registries continue to be queried, and the CLI shows a clear error.

Q: Can I host my own private registry?
A: Absolutely. Use the custom registry plugin interface. We provide a reference implementation.


⚠️ Disclaimer

SkillFetch Reloaded is provided "as is" without warranty of any kind, express or implied. While the AI security labeling system uses advanced pattern recognition and analysis, no automated system can guarantee 100% security. Users are strongly encouraged to:

  • Review code from experimental or risky-labeled skills before installation
  • Run unknown skills in a sandboxed environment
  • Regularly update installed skills to receive security patches
  • Never install skills from untrusted sources with elevated permissions

The developers assume no liability for damages arising from the use of this software or the skills discovered through it. Always practice safe coding habits. The year is 2026—defense in depth is not optional.


📬 Support & Community


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SkillFetch ReloadedYour agent's Swiss Army knife, delivered from every corner of the internet.

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