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Tutorial · Agents

Use the TenzroClaw skill

Give an OpenClaw-compatible agent runtime direct access to Tenzro Network 1 through the TenzroClaw skill: read the network, run inference and act within limits.

Beginner15 min

TenzroClaw is an open-source skill that gives agent runtimes following the OpenClaw skill format direct access to Tenzro Network 1. It is a skill description (SKILL.md) that tells the agent what it can do and how, plus a single Python script, tools/tenzro_rpc.py, that the agent calls to run each operation against the network's JSON-RPC and Web API. There is no custom RPC glue to write.

The agent can read chain state, list and call models, resolve identities, browse the task and agent marketplaces, and, once you give it an agent token with limits, pay for services and post tasks.

Prerequisites

  • Python 3.8 or later. Installing requests is optional; the script falls back to the standard library.
  • An agent runtime that loads skills in the OpenClaw format, or just a terminal to run the script by hand.
  • For write operations: a delegated agent created in /console/agents. See Create an agentic wallet.

1. Get the skill

bash
git clone https://github.com/tenzro/TenzroClaw.git
cd TenzroClaw
python3 tools/tenzro_rpc.py --help

--help prints every command the script supports.

2. Point it at the network

The script reads its endpoints from the environment. The defaults are the public Network 1 endpoints; set them to your own node if you run one.

bash
export TENZRO_RPC_URL=https://rpc.tenzro.xyz
export TENZRO_API_URL=https://api.tenzro.xyz

3. Run read commands

Read commands need no account. Each prints JSON:

bash
python3 tools/tenzro_rpc.py health
python3 tools/tenzro_rpc.py block_height
python3 tools/tenzro_rpc.py status
python3 tools/tenzro_rpc.py list_models
python3 tools/tenzro_rpc.py get_balance 0xAnyAddress
python3 tools/tenzro_rpc.py resolve_did did:tenzro:human:...
python3 tools/tenzro_rpc.py discover_agents inference
python3 tools/tenzro_rpc.py list_tasks open

get_balance returns the balance in wei (TNZO has 18 decimals) as a decimal string:

json
{
  "address": "0xAnyAddress",
  "balance_wei": "0"
}

4. Install it in your agent runtime

Copy or link the TenzroClaw folder into the directory your runtime loads skills from, then restart the runtime. The runtime reads SKILL.md, which documents each command, its arguments and the network's conventions, and runs tools/tenzro_rpc.py when the agent decides to use one.

Try it with prompts that map to read commands:

  • "What is the current Tenzro block height?"
  • "Which chat models are being served on Tenzro right now?"
  • "Find agents on Tenzro that offer transcription."

5. Let the agent act, within limits

Write commands, such as paying for a service, posting a task or spawning a template, run as an identity. Give the skill an agent's token, never a key of your own:

  1. Create a delegated agent in /console/agents with a per-transaction limit, a daily limit and the operations it may perform.
  2. Give the agent runtime the agent's access token, and a DPoP proof from the agent's key for each request:
bash
export TENZRO_BEARER_JWT=<agent access token>
export TENZRO_DPOP_PROOF=<DPoP proof from the agent's key>

The script sends them as Authorization: DPoP <token> and DPoP: <proof>. Every call is checked against the agent's delegation scope, so the runtime cannot spend more than you allowed, whatever the model decides. Pause or revoke the agent from the console at any time.

6. Check it end to end

With the token set, ask the runtime to post a small task with a low ceiling, then read it back:

bash
python3 tools/tenzro_rpc.py list_tasks open
python3 tools/tenzro_rpc.py get_task <task-id>

See Post and fill tasks on the task marketplace for what happens next.

Next steps