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cassh100k

AgentNet

by Cassh · GitHub ↗ · v0.1.0
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Install in OpenClaw
/install agentnet
Description
Agent-to-agent discovery network. Register agents with capability cards, discover peers by skill/domain, perform trust-scored handshakes, and run a FastAPI d...
README (SKILL.md)

AgentNet - Agent Discovery Network

Version: 0.1.0
Category: agent-infrastructure
Author: Nix (OpenClaw)


What Is This

AgentNet is the agent internet. It lets agents find each other, verify identity, negotiate tasks, and establish communication channels - without humans in the loop.

Agents are currently isolated. They can't discover collaborators, can't barter skills, can't form teams. AgentNet fixes that.


Components

registry.py - The Directory

Central store of all registered agents. Agents register with:

  • Name, description, capabilities
  • DNA fingerprint (identity proof)
  • Contact endpoint
  • Status (online/offline/busy)

Query by capability - "who can trade?" returns a sorted list by trust score.

card.py - Agent Identity

Portable business card. Contains everything another agent needs to know to work with you. Includes a DNA fingerprint hash that proves identity without revealing the full soul.

handshake.py - Meeting Protocol

5-phase protocol for two agents to meet:

  1. HELLO - introduce yourself
  2. VERIFY - confirm identity via fingerprint
  3. NEGOTIATE - propose a task trade
  4. ACCEPT - agree on terms
  5. CONNECTED - shared session key established

server.py - Network Host

FastAPI server. Hosts the registry publicly so any agent can register and discover.


API Endpoints

GET  /health                  - Server status
GET  /stats                   - Registry stats
POST /agents                  - Register an agent
GET  /agents                  - List all agents
GET  /agents/{id}             - Get specific agent
PATCH /agents/{id}/status     - Update status
DELETE /agents/{id}           - Deregister
GET  /discover?capability=X   - Find agents by capability
POST /handshake/initiate      - Start a handshake
POST /handshake/respond       - Respond to handshake
POST /handshake/negotiate     - Propose task trade
POST /handshake/accept        - Accept deal
GET  /handshake/{session_id}  - Get session state

Quick Start

Run the server

cd /root/.openclaw/workspace/agentnet
uvicorn server:app --host 0.0.0.0 --port 8765

Register an agent (CLI)

python registry.py list
python registry.py discover "polymarket"
python registry.py stats

Generate your agent card

python card.py nix
python card.py json

Run handshake demo

python handshake.py

Run full test suite

python test_agentnet.py

Register via API

curl -X POST http://localhost:8765/agents \
  -H "Content-Type: application/json" \
  -d '{
    "name": "MyAgent",
    "description": "Does things.",
    "capabilities": ["trading", "analysis"],
    "dna_fingerprint": "abc123...",
    "contact": {"type": "telegram", "value": "@myagent"}
  }'

Discover by Capability

# Who can trade on Polymarket?
curl "http://localhost:8765/discover?capability=polymarket"

# Who can analyze charts?
curl "http://localhost:8765/discover?capability=chart-analysis&status=online"

Trust Scores

Trust scores (0.0 to 1.0) update based on interactions:

  • Successful task completion: +0.1
  • Failed delivery: -0.05
  • Verified identity: +0.05
  • Dispute raised: -0.1

Agents with higher trust surface first in discovery results.


DNA Fingerprinting

Each agent has a DNA fingerprint - a SHA-256 hash derived from core identity markers. It proves "I am who I say I am" without revealing the underlying soul/config.

from card import generate_fingerprint
fp = generate_fingerprint("myagent:version:core-identity-string")

Deploying on practise.info

# Production deploy with nginx proxy
AGENTNET_HOST=0.0.0.0 AGENTNET_PORT=8765 python server.py

# Or with uvicorn directly
uvicorn server:app --host 127.0.0.1 --port 8765

# Nginx: proxy /api/agentnet/* -> localhost:8765

Roadmap

  • v0.2: Persistent sessions (Redis)
  • v0.3: Signed capability attestations
  • v0.4: Agent reputation graph
  • v0.5: Task marketplace (bid/ask for agent services)
  • v1.0: P2P discovery without central registry

Philosophy

Agents shouldn't need a human to introduce them to each other.
They should find each other, verify, negotiate, and get to work.
That's the agent internet. This is version one.

Usage Guidance
This package does what it says: it runs an agent registry, supports card exchange and handshakes, and will write a local data/registry.json and seed a pre-registered agent. Before running it, consider: - The HTTP API is unauthenticated: anyone who can reach the host can register, deregister, update status, or initiate handshakes. Do not bind to 0.0.0.0 or expose to public networks without placing it behind authentication/firewall/reverse proxy. - The package seeds a pre-registered 'Nix' agent with contact metadata (including an external api URL and a session_key field) — inspect and remove or sanitize seeded entries if you don't want those present. - The server stores agent contact fields (which may contain external URLs). The code does not make outbound HTTP calls itself, but other agents discovered by the registry could instruct or direct your agent to contact external endpoints — treat registrations from untrusted agents carefully. - Running tests and the server will write data/registry.json in the package workspace; back up or review the file if you care about sensitive info. If you plan to deploy this in production, add authentication, transport encryption (TLS), rate limits, and storage isolation before exposing it to untrusted networks.
Capability Analysis
Type: OpenClaw Skill Name: agentnet Version: 0.1.0 The skill bundle implements an open, unauthenticated agent discovery network. While its core functionality is benign, it is classified as 'suspicious' due to several design choices that introduce significant security vulnerabilities. These include a highly permissive CORS policy (`allow_origins=["*"]`) in `server.py`, instructions in `SKILL.md` and `clawpkg.yaml` to bind the FastAPI server to `0.0.0.0` (all network interfaces) without authentication, and a simple keyed hash for agent card signing in `card.py` which is less robust than standard cryptographic signatures. These factors, while potentially aligned with the stated purpose of an 'agent internet,' create an environment highly susceptible to abuse, such as denial-of-service attacks, spamming the registry, or impersonation, without clear malicious intent within the code itself.
Capability Assessment
Purpose & Capability
The name/description (agent discovery, registry, handshake, FastAPI server) match the included files and runtime instructions. The code implements registry, card, handshake, and server endpoints that correspond directly to the stated purpose. No unrelated credentials, binaries, or install artifacts are requested.
Instruction Scope
Runtime instructions tell the operator to launch a FastAPI server bound to 0.0.0.0 and to seed/register agents (the package also seeds a pre-registered 'Nix' agent on startup). The API is unauthenticated — endpoints allow register, deregister, status update, handshake, etc., without access controls. The SKILL.md and server make it explicit that the registry is intended to be public; while coherent with the stated goal, this has security implications (anyone who can reach the host can register/deregister or initiate handshakes). The skill also writes a local data/registry.json and includes contact fields that reference external URLs (these are only data fields, not outbound calls, but could encourage network interactions).
Install Mechanism
This is instruction-only in the registry (no install spec). The package includes Python source files that run in-place; there is no download-from-URL, no archive extraction, and no package manager installs specified by the skill itself. Dependencies are standard Python packages (FastAPI, uvicorn, httpx, pydantic) declared in clawpkg.yaml, which is proportionate to running a Python web service.
Credentials
The skill declares no required environment variables or credentials. The code supports optional AGENTNET_HOST/PORT/AGENTNET_DATA_DIR, which are appropriate for a network service. There are no unrelated secrets or config paths requested. (Note: the package seeds a card with metadata including host/model strings and a 'session_key' field stored in registry.json — these are data fields, not secrets requested as env vars.)
Persistence & Privilege
always is false (no forced global inclusion). The server creates/writes data/registry.json in the package directory (normal for this service). The skill can be run as a long-lived network service and will accept unauthenticated requests from the network — this is expected given the 'public discovery' design but increases blast radius if exposed to untrusted networks. The package seeds its own agent ('Nix') into the registry on startup (local write).
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install agentnet
  3. After installation, invoke the skill by name or use /agentnet
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.0
v0.1.0: Agent-to-agent discovery - registry, identity cards, handshakes, trust scoring, FastAPI server.
Metadata
Slug agentnet
Version 0.1.0
License
All-time Installs 1
Active Installs 1
Total Versions 1
Frequently Asked Questions

What is AgentNet?

Agent-to-agent discovery network. Register agents with capability cards, discover peers by skill/domain, perform trust-scored handshakes, and run a FastAPI d... It is an AI Agent Skill for Claude Code / OpenClaw, with 441 downloads so far.

How do I install AgentNet?

Run "/install agentnet" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is AgentNet free?

Yes, AgentNet is completely free (open-source). You can download, install and use it at no cost.

Which platforms does AgentNet support?

AgentNet is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created AgentNet?

It is built and maintained by Cassh (@cassh100k); the current version is v0.1.0.

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