web3-agent-reputation 0.1.0

ERC-8004 Trustless Agents: web3.py external module (facts layer) + a pure reputation calculator

web3-agent-reputation

ERC-8004 Trustless Agents — a web3.py external module (facts layer) plus a pure reputation calculator. The Python member of the agent-reputation-sdk family; numerically identical to the TypeScript agent-reputation package against the shared golden vectors in vectors/.

Install

pip install web3-agent-reputation
# or, in this repo, from the packages/py directory:
uv sync

Requires Python >=3.10 and web3>=6.

The two-layer contract

Facts layer — thin typed reads through your existing Web3 client; no opinions:

from web3 import Web3
from web3_agent_reputation import ERC8004Module

w3 = Web3(Web3.HTTPProvider("https://mainnet.base.org"),
          external_modules={"erc8004": ERC8004Module})
# or, post-construction: w3.attach_modules({"erc8004": ERC8004Module})

agent = w3.erc8004.get_agent(1)                  # Agent(agent_id, owner, token_uri, registered_at)
feedback = w3.erc8004.get_agent_feedback(1)       # list[FeedbackEntry]
validations = w3.erc8004.get_agent_validations(1) # list[ValidationEntry]
reg_file = w3.erc8004.get_registration_file(1)    # verified: True | False | None

Chain detection is automatic (w3.eth.chain_id at call time) against a 7-chain ERC-8004 registry table (Ethereum, Base, Polygon, Arbitrum, Optimism, BNB, Gnosis) — an unsupported chain raises ChainUnsupportedError.

Calculator layer

A pure function; your policy in, evidence-rich result out — never a bare scalar. Every result carries expectation, uncertainty, witness statistics, honesty caveats, and the echoed policy (the reproducibility manifest):

from web3_agent_reputation import calculate_reputation, activity_sqrt

rep = calculate_reputation(feedback, witness_cap=1, credibility=activity_sqrt(distinct_counts))
# Reputation(expectation=0.665, uncertainty=0.179, witnesses=20, entries=..., 
#            top_witness_share=0.15, caveats=[...], policy={...})

calculate_reputation accepts anything with .client/.score attributes (including the FeedbackEntry returned by get_agent_feedback directly) — see src/web3_agent_reputation/calculator.py for the full normative algorithm description, copied verbatim from the TypeScript reference.

The no-bare-scalar principle

A single reputation number invites false confidence: it hides how many witnesses backed it, whether one dominant client inflated it, and what policy produced it. Every Reputation this package returns is a small evidence bundle instead — witnesses, entries, top_witness_share, and caveats travel with expectation/uncertainty so a caller can judge how much to trust the number, not just read the number. The calculator computes what you asked for under a policy you declared; it does not define "the" score for any agent — judgment stays with the consumer.

Errors

Erc8004Error is the base class; subclasses are AgentNotFoundError, ChainUnsupportedError, RpcError, FileUnreachableError, FileHashMismatchError, InvalidInputError. See src/web3_agent_reputation/errors.py.

Tests

uv run pytest              # unit + golden-vector conformance, no network
uv run pytest -m live       # live smoke test against Base public RPC (deselected by default)

Example

examples/vet_agent.py — given an agent id and a chain RPC URL, prints the facts and calculated reputation (both variants) for that agent: a pre-delegation guard in ~40 lines.

uv run python examples/vet_agent.py --agent-id 1 --rpc-url https://mainnet.base.org