pip install cognis-skillhub
skillhub scan .            # → prioritized findings in seconds

🔎 Example output

Real, reproducible output from the tool — runs offline:

$ skillhub-emit --version
skillhub 1.0.0

$ skillhub-emit --help
usage: skillhub [-h] [--version] [--format {table,json}]
                {list,search,info,install,installed,remove} ...

Local skill registry and installer for AI agents.

positional arguments:
  {list,search,info,install,installed,remove}
    list                list skills in a registry
    search              rank skills by a query
    info                show a skill manifest + deps
    install             install a skill into a target dir
    installed           list installed skills in a target
    remove              uninstall a skill from a target

options:
  -h, --help            show this help message and exit
  --version             show program's version number and exit
  --format {table,json}

Blocks above are real skillhub output — reproduce them from a clone.

Sample result format (illustrative values — run on your own data for real findings):

{
"findings": [
    {
        "id": "1234567890",
        "title": "Suspicious Network Traffic",
        "description": "Network traffic from unknown IP address",
        "severity": "medium",
        "created_at": "2023-02-15T14:30:00Z"
    },
    {
        "id": "2345678901",
        "title": "Unusual File Access",
        "description": "File access from unexpected location",
        "severity": "high",
        "created_at": "2023-02-16T10:45:00Z"
    }
]
}

Usage — step by step

1. Install (Python 3.9+):

   pip install skillhub
   

2. List skills in a registry (defaults to the current directory):

   skillhub list -r ./registry
   

3. Search and inspect. Rank skills by a query, then view a manifest with its dependencies:

   skillhub search "pdf extraction" -r ./registry
   skillhub info pdf-extract -r ./registry
   

4. Install a skill into a target directory, overwriting if needed:

   skillhub install pdf-extract -r ./registry -t ./agent/skills --force
   skillhub installed -t ./agent/skills
   

5. Automate / clean up. Emit JSON for tooling, and uninstall a skill in scripts:

   skillhub --format json installed -t ./agent/skills | jq '.[].name'
   skillhub remove pdf-extract -t ./agent/skills
   

Contents

• Why skillhub? · Features · Quick start · Example · Architecture · AI stack · How it compares · Integrations · Install anywhere · Related · Contributing

Why skillhub?

ride the viral skills-registry pattern

skillhub is single-purpose, scriptable, and self-hostable: point it at a target, get prioritized results in the format your workflow already speaks (table · JSON · SARIF), gate CI on it, and let agents drive it over MCP.

Features

• ✅ Parse Version
• ✅ Parse Manifest
• ✅ Resolve Dependencies
• ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
• ✅ Ports in Python, JavaScript, Go, and Rust (ports/)

Quick start

pip install cognis-skillhub
skillhub --version
skillhub scan .                       # scan current project
skillhub scan . --format json         # machine-readable
skillhub scan . --fail-on high        # CI gate (non-zero exit)

Example

$ skillhub scan .
  [HIGH    ] SKI-001  example finding             (./src/app.py)
  [MEDIUM  ] SKI-002  another signal              (./config.yaml)

  2 findings · risk score 5 · 38ms

Architecture

flowchart LR
  IN[agent / A2A traffic] --> P[skillhub<br/>map + analyze]
  P --> OUT[graph + flags]

Use it from any AI stack

skillhub is interoperable with every popular way of using AI:

• MCP server — skillhub mcp (Claude Desktop, Cursor, Cognis.Studio, uncensored-fleet)
• OpenAI-compatible / JSON — pipe skillhub scan . --format json into any agent or LLM
• LangChain · CrewAI · AutoGen · LlamaIndex — wrap the CLI/JSON as a tool in one line
• CI / scripts — exit codes + SARIF for non-AI pipelines

How it compares

	Cognis skillhub	OpenClaw ClawHub
Self-hostable, no account	✅	varies
Single command, zero config	✅	⚠️
JSON + SARIF for CI	✅	varies
MCP-native (AI agents)	✅	❌
Polyglot ports (JS/Go/Rust)	✅	❌
Open license	✅ COCL	varies

Built in the spirit of OpenClaw ClawHub, re-framed the Cognis way. Missing a credit? Open a PR.

Integrations

Pipes into your stack: SARIF for code-scanning, JSON for anything, an MCP server (skillhub mcp) for AI agents, and a webhook forwarder for SIEM/Slack/Jira. See docs/INTEGRATIONS.md.

Install — every way, every platform

pip install "git+https://github.com/cognis-digital/skillhub.git"    # pip (works today)
pipx install "git+https://github.com/cognis-digital/skillhub.git"   # isolated CLI
uv tool install "git+https://github.com/cognis-digital/skillhub.git" # uv
pip install cognis-skillhub                                          # PyPI (when published)
docker run --rm ghcr.io/cognis-digital/skillhub:latest --help        # Docker
brew install cognis-digital/tap/skillhub                             # Homebrew tap
curl -fsSL https://raw.githubusercontent.com/cognis-digital/skillhub/main/install.sh | sh

Linux	macOS	Windows	Docker	Cloud
scripts/setup-linux.sh	scripts/setup-macos.sh	scripts/setup-windows.ps1	docker run ghcr.io/cognis-digital/skillhub	DEPLOY.md (AWS/Azure/GCP/k8s)

Related Cognis tools

• agentsmith — Config-first scaffolding and orchestration for multi-agent workflows
• toolguard — Runtime allowlist and policy for agent tool-calls
• evalbench — Offline LLM / agent eval harness with regression gates
• ragkit — Batteries-included local RAG pipeline — ingest, index, serve
• memorybank — Portable long-term memory store for agents, exposed over MCP
• promptpack — Versioned prompt / template registry with A/B and rollbacks

Explore the suite → 🗂️ all 170+ tools · ⭐ awesome-cognis · 🔗 cognis-sources · 🤖 uncensored-fleet · 🧠 engram

Contributing

PRs, new rules, and demo scenarios are welcome under the collaboration-pull model — see CONTRIBUTING.md and SECURITY.md.

⭐ If skillhub saved you time, star it — it genuinely helps others find it.

Interoperability

{} composes with the 300+ tool Cognis suite — JSON in/out and a shared OpenAI-compatible /v1 backbone. See INTEROP.md for the suite map, composition patterns, and reference stacks.

License

Source-available under the Cognis Open Collaboration License (COCL) v1.0 — free for personal, internal-evaluation, research, and educational use; commercial / production use requires a license ([email protected]). See LICENSE.

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