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Reputation intelligence for AI agents — trust scores, Sybil detection, cross-chain identity

Project description

trustlayer

Reputation intelligence for AI agents. Trust scores, Sybil detection, and cross-chain identity resolution for 133K+ agents across 20 blockchains.

Install

pip install trustlayer

With LangChain support:

pip install trustlayer[langchain]

With CrewAI support:

pip install trustlayer[crewai]

Quick Start

from trustlayer import TrustLayer

tl = TrustLayer()
report = tl.trust("base:1378")
print(report["trust_score"])      # 73
print(report["sybil_risk"])       # "medium"
print(report["risk_level"])       # "medium"

Async

from trustlayer import AsyncTrustLayer

async with AsyncTrustLayer() as tl:
    report = await tl.trust("base:1378")

LangChain

from trustlayer.tools import as_langchain_tools

tools = as_langchain_tools()
# Add to your agent
agent = create_react_agent(llm, tools)

CrewAI

from trustlayer.tools import as_crewai_tools

tools = as_crewai_tools()
# Add to your agent
agent = Agent(role="Risk Analyst", tools=tools)

Standalone Tool Functions

from trustlayer.tools import check_agent_trust, get_top_agents

# Check before transacting with an agent
print(check_agent_trust("base:1378"))
# Agent: QuickNick (base:1378)
# Trust Score: 73/100
# Risk Level: medium
# Sybil Risk: medium

# Get top agents
print(get_top_agents("base", limit=5))

API Methods

Method Description Rate Limit
trust(agent_id) Full Sybil forensics report 5 req/hr (free demo)
score(agent_id) Basic trust score 5 req/hr (free demo)
solana(address) Solana wallet scoring x402 $0.001
leaderboard(chain, limit) Top agents 5 req/hr
stats() Network stats Unlimited

Agent IDs use chain:id format: base:1378, ethereum:42, bsc:100, polygon:56, monad:1000.

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