autoresearch-coordinator

name	autoresearch-coordinator
description	Coordinate distributed autoresearch experiments across GPU workers discovered via ERC-8004 and paid via x402 micropayments.
metadata	{"openclaw":{"emoji":"🔬","requires":{"bins":["python3","curl"]}}}

Autoresearch Coordinator

Coordinate distributed autoresearch experiments across GPU workers discovered on-chain via ERC-8004 and paid per-experiment via x402 micropayments. This replaces the Ensue-based shared-memory coordinator from autoresearch-at-home with a fully decentralised discovery and payment loop built on obol-stack primitives.

When to Use

• Discovering GPU workers advertising devops_mlops/model_versioning capabilities via the 8004scan public index API
• Probing worker endpoints for x402 pricing before submitting experiments
• Submitting train.py experiments to remote GPU workers through x402 payment gates
• Running the continuous THINK/CLAIM/RUN/PUBLISH experiment loop
• Viewing the global leaderboard of autoresearch results from worker metadata
• Coordinating multi-worker experiment campaigns

When NOT to Use

• Selling your own GPU as a worker -- use autoresearch-worker (then monetize it with obol sell http)
• Buying generic inference (chat completions) -- use buy-x402
• Discovering agents without running experiments -- use discovery
• Signing transactions directly -- use ethereum-local-wallet
• Cluster diagnostics -- use obol-stack

Quick Start

# Discover available GPU workers from the preferred public index API
python3 scripts/coordinate.py discover

# Discover with custom limit
python3 scripts/coordinate.py discover --limit 5

# Probe a specific worker for pricing
python3 scripts/coordinate.py probe https://worker.example.com/services/autoresearch-worker

# Submit a single experiment to a worker
python3 scripts/coordinate.py submit https://worker.example.com/services/autoresearch-worker train.py

# Submit with custom config overrides
python3 scripts/coordinate.py submit https://worker.example.com/services/autoresearch-worker train.py \
  --config '{"batch_size": 64, "learning_rate": 0.001}'

# View global leaderboard (best val_bpb across all workers)
python3 scripts/coordinate.py leaderboard

# Run continuous experiment loop (discover -> pick -> submit -> publish)
python3 scripts/coordinate.py loop train.py

# Loop with worker preference and max rounds
python3 scripts/coordinate.py loop train.py --prefer https://worker.example.com/services/autoresearch-worker --rounds 10

Commands

Command	Description
discover [--limit N]	Query the preferred public index API for GPU workers with devops_mlops/model_versioning skill
probe <endpoint>	Send unauthenticated request to parse 402 pricing from the worker
submit <endpoint> <train.py> [--config JSON]	Submit experiment with x402 payment (pre-sign ERC-3009, attach X-PAYMENT)
leaderboard [--limit N]	Query 8004scan for all autoresearch workers, rank by best val_bpb
loop <train.py> [--prefer URL] [--rounds N]	Continuous loop: discover, pick best worker, submit, collect, publish

The Experiment Loop

The coordinator implements a THINK/CLAIM/RUN/PUBLISH loop:

1. THINK -- Read current train.py, review leaderboard results, decide on next experiment variation
2. CLAIM -- Discover workers via 8004scan, probe pricing, select best worker (cheapest or preferred)
3. RUN -- Submit train.py + config to worker via POST /experiment through the x402 payment gate
4. PUBLISH -- Record result locally with provenance metadata (val_bpb, experiment_id, train.py hash, worker endpoint)

Each step is atomic and idempotent. If a worker fails mid-experiment, the coordinator retries with the next available worker.

How Discovery Works

Workers register on-chain via ERC-8004 and advertise capabilities through OASF (Open Agent Skills Framework) metadata. The coordinator discovers workers via the public 8004scan API:

GET https://www.8004scan.io/api/v1/public/agents
    ?protocol=OASF
    &search=devops_mlops/model_versioning
    &limit=20

The API returns agent summary objects. The coordinator then prefers the embedded registration document in raw_metadata.offchain_content and falls back to the off-chain registration URI when needed.

From the registration document it extracts:

• service endpoints (where to POST experiments)
• x402 support flag (payment-gated access)
• OASF capability metadata from the services[] entry with name: OASF
• leaderboard metadata such as best_val_bpb

How Payment Works

Experiment submission uses the same x402 payment flow as buy-x402:

1. Probe -- Send unauthenticated POST to worker endpoint, receive 402 Payment Required with pricing
2. Sign -- Pre-sign an ERC-3009 TransferWithAuthorization voucher via the current remote-signer API (GET /api/v1/keys, POST /api/v1/sign/<address>/typed-data)
3. Submit -- Re-send the POST with the X-PAYMENT header containing the signed voucher
4. Settle -- Worker's x402 verifier validates payment via the facilitator, forwards request to GPU

Payment is per-experiment (not per-token). The 402 response includes amount in the v2 wire format; legacy sellers may still return maxAmountRequired.

How Results are Published

After collecting a result from a worker, the coordinator stores provenance metadata locally:

{
  "experiment_id": "exp-20260312-a1b2c3",
  "train_hash": "sha256:abcdef...",
  "val_bpb": 1.234,
  "worker_endpoint": "https://worker.example.com/services/autoresearch",
  "worker_agent_id": 42,
  "timestamp": "2026-03-12T10:30:00Z",
  "payment_tx": "0xdeadbeef..."
}

Results are appended to $DATA_DIR/autoresearch/results.jsonl (one JSON object per line).

Environment Variables

Variable	Default	Description
SCAN_API_URL	https://www.8004scan.io/api/v1/public	Public 8004scan API base URL for worker discovery
REMOTE_SIGNER_URL	http://remote-signer:9000	Remote-signer REST API for payment signing
ERPC_URL	http://erpc.erpc.svc.cluster.local:4000/rpc	eRPC gateway base URL
ERPC_NETWORK	base	Default chain for payment
DATA_DIR	/data	Base directory for result storage

Architecture

coordinate.py
    |
    +-- discover: 8004scan API (OASF filter)
    |       |
    |       v
    |   Worker .well-known/agent-registration.json
    |
    +-- probe: POST /experiment (no payment)
    |       |
    |       v
    |   402 Payment Required (pricing JSON)
    |
    +-- submit: ERC-3009 sign via remote-signer
    |       |
    |       +-- POST /experiment + X-PAYMENT header
    |       |       |
    |       |       v
    |       |   x402 verifier -> facilitator -> GPU worker
    |       |       |
    |       |       v
    |       |   200 + experiment result
    |       |
    |       v
    +-- publish: results.jsonl (local provenance)

Constraints

• Requires remote-signer -- must have agent wallet provisioned via obol openclaw onboard
• Requires network access -- 8004scan API and worker endpoints must be reachable
• Python stdlib only -- uses urllib; no third-party Python dependencies required
• Per-experiment payment -- each submission costs one x402 payment; monitor balance via buy-x402 balance
• Worker availability -- workers may go offline between discovery and submission; coordinator retries automatically
• Result storage is local -- provenance metadata stored on-disk, not on-chain (future: IPFS/on-chain attestations)

References

• references/coordination-protocol.md -- Ensue-to-obol mapping, discovery flow, payment flow, leaderboard format
• See also: discovery skill for raw ERC-8004 registry queries
• See also: buy-x402 skill for the x402 buyer sidecar architecture
• See also: sell skill for running a GPU worker (sell-side)