SkillNet: The Operating System for AI Skills

pip install skillnet-ai

from skillnet_ai import SkillNetClient

client = SkillNetClient()

results = client.search("pdf understanding", limit=5)
print(results[0].skill_name)
print(results[0].skill_url)

client.download(url=results[0].skill_url, target_dir="./my_skills")

skillnet search "pdf understanding" --limit 5
skillnet download <skill_url> -d ./my_skills

git clone https://github.com/zjunlp/SkillNet.git
cd SkillNet

mkdir -p ~/.claude/skills
cp -R skills/skillnet ~/.claude/skills/skillnet

mkdir -p .claude/skills
cp -R /path/to/SkillNet/skills/skillnet .claude/skills/skillnet

Use SkillNet to search for a docker skill and summarize the top result.

git clone https://github.com/zjunlp/SkillNet.git
cd SkillNet

CODEX_HOME="${CODEX_HOME:-$HOME/.codex}"
mkdir -p "$CODEX_HOME/skills"
cp -R skills/skillnet "$CODEX_HOME/skills/skillnet"

Use $skillnet to search for a LangGraph skill before planning this task.

from skillnet_ai import SkillNetClient

client = SkillNetClient(
    api_key="YOUR_API_KEY",          # Required for create, evaluate, and analyze
    # base_url="https://api.openai.com/v1",
    # github_token="YOUR_GITHUB_TOKEN"
)

# Keyword search
results = client.search(q="pdf", limit=10, min_stars=5, sort_by="stars")

# Semantic search
results = client.search(
    q="analyze financial PDF reports",
    mode="vector",
    threshold=0.85,
)

if results:
    print(results[0].skill_name)
    print(results[0].skill_url)

local_path = client.download(
    url="https://github.com/anthropics/skills/tree/main/skills/skill-creator",
    target_dir="./my_skills",
)
print(local_path)

# From a conversation log or execution trace
client.create(
    trajectory_content="User: rename .jpg to .png\nAgent: Done.",
    output_dir="./skills",
)

# From a GitHub repository
client.create(github_url="https://github.com/zjunlp/DeepKE", output_dir="./skills")

# From an office document: PDF, PPT, or Word
client.create(office_file="./guide.pdf", output_dir="./skills")

# From a natural language prompt
client.create(prompt="A skill for web scraping article titles", output_dir="./skills")

result = client.evaluate(
    target="https://github.com/anthropics/skills/tree/main/skills/algorithmic-art"
)

print(result["safety"]["level"])
print(result["executability"]["reason"])

relationships = client.analyze(skills_dir="./my_skills")

for rel in relationships:
    print(f"{rel['source']} --[{rel['type']}]--> {rel['target']}")

skillnet search "pdf"
skillnet search "analyze financial reports" --mode vector --threshold 0.85
skillnet search "visualization" --category "Development" --sort-by stars --limit 10

skillnet download https://github.com/anthropics/skills/tree/main/skills/algorithmic-art
skillnet download <url> -d ./my_agent/skills
skillnet download <private_url> --token <your_github_token>
skillnet download <url> --mirror https://ghfast.top/

skillnet create ./logs/trajectory.txt -d ./generated_skills
skillnet create --github https://github.com/owner/repo
skillnet create --office ./docs/guide.pdf
skillnet create --prompt "A skill for extracting tables from images"

skillnet evaluate https://github.com/anthropics/skills/tree/main/skills/algorithmic-art
skillnet evaluate ./my_skills/web_search
skillnet evaluate ./my_skills/tool --category "Development" --model gpt-4o

skillnet analyze ./my_agent_skills
skillnet analyze ./my_agent_skills --no-save
skillnet analyze ./my_agent_skills --model gpt-4o

export API_KEY="YOUR_API_KEY"
export BASE_URL="https://..."

$env:API_KEY = "YOUR_API_KEY"
$env:BASE_URL = "https://..."

# Keyword search
curl "http://api-skillnet.openkg.cn/v1/search?q=pdf&sort_by=stars&limit=5"

# Semantic search
curl "http://api-skillnet.openkg.cn/v1/search?q=reading%20charts&mode=vector&threshold=0.8"

cd experiments

python alfworld_run.py --model o4-mini --split dev --max_workers 10 --exp_name alf_test --use_skill
python scienceworld_run.py --model o4-mini --split test --max_workers 5 --exp_name sci_test --use_skill
python webshop_run.py --model o4-mini --max_workers 3 --exp_name web_test --use_skill

npm i -g clawhub
clawhub install skillnet --workdir ~/.openclaw/workspace
openclaw gateway restart

Install the skillnet skill from ClawHub.

{
  "skills": {
    "entries": {
      "skillnet": {
        "enabled": true,
        "apiKey": "YOUR_API_KEY",
        "env": {
          "BASE_URL": "https://api.openai.com/v1",
          "GITHUB_TOKEN": "YOUR_GITHUB_TOKEN"
        }
      }
    }
  }
}

git clone https://github.com/CycleChain/skillnet-mcp
cd skillnet-mcp
npm install && npm run build

docker pull fmdogancan/skillnet-mcp:latest

{
  "mcpServers": {
    "skillnet": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "fmdogancan/skillnet-mcp:latest"],
      "env": {
        "API_KEY": "YOUR_API_KEY"
      }
    }
  }
}

@misc{liang2026skillnetcreateevaluateconnect,
      title={SkillNet: Create, Evaluate, and Connect AI Skills},
      author={Yuan Liang and Ruobin Zhong and Haoming Xu and Chen Jiang and Yi Zhong and Runnan Fang and Jia-Chen Gu and Shumin Deng and Yunzhi Yao and Mengru Wang and Shuofei Qiao and Xin Xu and Tongtong Wu and Kun Wang and Yang Liu and Zhen Bi and Jungang Lou and Yuchen Eleanor Jiang and Hangcheng Zhu and Gang Yu and Haiwen Hong and Longtao Huang and Hui Xue and Chenxi Wang and Yijun Wang and Zifei Shan and Xi Chen and Zhaopeng Tu and Feiyu Xiong and Xin Xie and Peng Zhang and Zhengke Gui and Lei Liang and Jun Zhou and Chiyu Wu and Jin Shang and Yu Gong and Junyu Lin and Changliang Xu and Hongjie Deng and Wen Zhang and Keyan Ding and Qiang Zhang and Fei Huang and Ningyu Zhang and Jeff Z. Pan and Guilin Qi and Haofen Wang and Huajun Chen},
      year={2026},
      eprint={2603.04448},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2603.04448}
}