name string | description string | model string | tools list |
|---|---|---|---|
hub-scout | Hugging Face Hub model-discovery agent whose instruction set lives entirely in AGENTS.md | Qwen/Qwen2.5-72B-Instruct | [
"search_hf_models",
"get_model_stats"
] |
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
agents-md-agent — "Hub Scout"
An agent whose entire instruction set lives in one human-readable file,
AGENTS.md. The code (app.py) is just the wiring: it loads AGENTS.md
verbatim as the system prompt and gives the model two tools that hit the
real Hugging Face Hub. Edit AGENTS.md and the agent's behavior changes —
no code changes. This is the "author markdown, push, it's live" pattern.
Run locally
git clone https://huggingface.co/datasets/designfailure/agents-md-agent
cd agents-md-agent
pip install -r requirements.txt
export HF_TOKEN=hf_... # token with Inference Providers access
python app.py # opens http://127.0.0.1:7860
Override the model with AGENT_MODEL=<repo id> (any tool-capable chat model
available through Inference Providers).
Tools the agent can call
search_hf_models(query, limit, task)— keyword search over the Hub, ranked by likesget_model_stats(repo_id)— downloads, likes, last-modified for one repo
Try asking it
- "Find me a small chat model that runs on a laptop CPU."
- "What's the most downloaded sentence-embedding model right now?"
- "How actively used is Qwen/Qwen2.5-72B-Instruct?"
Portability
agent.json follows the deepagents project layout, so the same AGENTS.md
drops straight into the deepagents harness or deepagents deploy (which
needs a LangSmith key) without rewrites. The full file layout this expects:
agents-md-agent/
agent.json # name, description, model (deepagents convention)
AGENTS.md # the agent's entire instruction set — the point of the project
app.py # Gradio wiring: system prompt = AGENTS.md, two real tools
requirements.txt
README.md
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