AgentData — Executable Liquidity (endpoint #1)

A pay-per-call data endpoint for AI agents: size-aware exit cost, depeg risk, and liquidity fragility for a token on Base. Not raw prices — computed, normalized, decision-grade intelligence an agent needs before it acts. Settled in USDC via x402 (Phase 2). Sourced on-chain, so the derived data is cleanly redistributable.

Strategy, values, and roadmap live in CLAUDE.md. Decisions are logged in decisions/DECISION_LOG.md and decisions/adr/.

What it answers

"If I try to exit this position right now, what does it actually cost me, how much can I move before slippage blows past X bps, and how fragile is that liquidity?"

Three priced tiers (single source of truth in agentdata/api/pricing.py):

Tier	Contents	Mainnet price
quote	best-route exit cost for one size	$0.008
risk	exit cost + fragility (+ depeg for pegged assets) — default	$0.02
deep	risk + multi-size exit-cost curve + max-size-before-cost ladder	$0.04

Testnet forces every price to $0 (the 402 flow is still exercised end-to-end).

Layout

src/agentdata/
  config.py            # env-driven; NETWORK_MODE testnet|mainnet (testnet default)
  compute/             # the value-add: pure, deterministic, unit-tested math
    amm.py             #   constant-product + Solidly stable curve, exit cost
    routing.py         #   cheapest-venue selection
    depeg.py           #   depeg deviation / dispersion / score
    fragility.py       #   depth + concentration + convexity -> fragility score
    tiers.py           #   quote / risk / deep orchestration
  chain/               # on-chain Base reads (Aerodrome / Uniswap), web3 lazy
    provider.py        #   FixturePoolProvider (default) + factory
    onchain.py         #   OnChainPoolProvider (env-gated, no guessed addresses)
  api/                 # FastAPI JSON layer + pricing + stable schema
  monitoring/          # uptime, latency p50/p95, error rate, calls per tier
tests/                 # unittest (stdlib for compute; fastapi for api)

Run it (local, no funds, no network)

pip install -e .            # or: pip install fastapi pydantic 'uvicorn[standard]'
uvicorn agentdata.api.app:app --reload
# then:
curl 'http://127.0.0.1:8000/v1/liquidity/exit-cost?token=WETH&size=10&tier=risk'
curl 'http://127.0.0.1:8000/pricing'
curl 'http://127.0.0.1:8000/metrics'

Defaults: NETWORK_MODE=testnet, POOL_SOURCE=fixture (deterministic demo pools WETH, THIN, USDX). See .env.example.

Test

# compute core needs no dependencies:
PYTHONPATH=src python -m unittest discover -s tests

Status

Phase 1 (local endpoint): done. compute + chain seam + API + monitoring, 42 tests green.
Phase 2 (x402 testnet): next. Payment middleware in front of the API, free testnet facilitator on Base Sepolia. No real USDC; mainnet is an escalated human decision (CLAUDE.md §0/§14).
On-chain mode requires a verified pool registry before use (ADR-001) — the code refuses to run on guessed contract addresses rather than fake data.

AgentData - Executable Liquidity / Exit-Cost