Agent Veil Protocol — Trust Enforcement for Autonomous Agents

6 min read Original article ↗

● Production · pip install agentveil

Trust governance
for AI agents.
At every stage.

Full agent lifecycle — before they act, while they operate, after they finish.

>>> agent.can_trust("did:key:z6Mk...", min_tier="trusted")

{
  "allowed": true,
  "score": 0.82,
  "tier": "trusted",     ✓ TRUSTED
  "risk_level": "low"
}

>Use Cases

Prove your agent did its job

You deploy agents for clients. They need proof the agent did exactly what it was supposed to — without access to your infrastructure.

cred = agent.get_reputation_credential()  # client verifies offline

Multi-agent pipelines

Orchestrator delegates to sub-agents. Unknown sub-agents can’t inherit chain reputation.

agent.can_trust(sub_agent_did, min_tier="trusted")

Webhook alerts

Agents run 24/7. Get notified when any agent’s score drops below threshold before damage happens.

agent.set_alert(webhook_url, threshold=0.7)

Regulated environments

EU AI Act requires auditability. Every action signed, hash-chained, anchored to IPFS.

agent.get_audit_trail()  # export-ready, tamper-evident

>Trust Only Matters If It Changes Access

●Without AgentVeil

No identity — who is this agent?
No sponsor chain — who is it acting for?
No trust history — should it be allowed here?
No accountability — who owns the outcome?
No enforcement — what stops risky actions?
No input safety — injection and data leaks?

●With AgentVeil

Verified DID — cryptographic identity
Trust signals — attestations, history, and reputation
Admission decisions — trust before action
Audit trail — trace actions, outcomes, and sponsors
Dispute protection — contest unfair trust events
Input security — multi-layer input validation on every request

>What It Does

Verify Agent Identity

Ed25519 keys, W3C DID standard. One key = one portable, cryptographic identity across tools and protocols.

Collect Trust Signals

Signed attestations, peer reviews, GitHub verification, and execution history build trust over time.

Evaluate Trust

EigenTrust scoring, per-category tracks, velocity alerts, and anti-collusion checks help determine whether an agent should be trusted in context.

Enable Admission Decisions

Turn identity, attestations, and trust metadata into a decision: should this agent be allowed to act here?

Agent Cards

Publish capabilities, discover agents by skill, and evaluate trust before interaction.

Verifiable Audit Trails

Every attestation is signed, tamper-evident, and permanently anchored to IPFS.

Dispute Protection

Contest unfair negative ratings and resolve trust conflicts through evidence-based review.

>How It Works

Before

Admission Gate

Identity verification
Trust check
Admission decision

→

During

Continuous Monitoring

Real-time attestations
Risk scoring
Webhook alerts

→

After

Forensic Record

Audit trail
Dispute resolution
Signed credentials

>Integrations

⚙ CrewAI

⚡ LangGraph

⚙ AutoGen

✨ Claude

◆ OpenAI

📎 Paperclip

🐍 Any Python

Works across your agent stack — open identity standards, portable trust, and complementary enforcement layers.

>Explorer

Real-time data from production API

Agents

Attestations

Audit Log

Click any agent to view details

AgentCapabilitiesProviderScore
Loading...

Select an agent to view attestations

Select an agent to view audit trail

>API

Production endpoints at agentveil.dev

Method Endpoint Description
GET/reputation/{did}Score, confidence, risk assessment
GET/reputation/{did}/trust-checkAdvisory trust decision
GET/reputation/{did}/credentialSigned offline credential (Ed25519)
GET/reputation/{did}/velocityScore trend (1d/7d/30d)
POST/attestationsSubmit peer rating
POST/attestations/batchBatch ratings (up to 50)
POST/agents/registerRegister new agent
GET/cardsSearch agents by capability
GET/audit/verifyChain integrity check

SDK: github.com/creatorrmode-lead/avp-sdk · PyPI

>Quick Start

pip install agentveil


from agentveil import AVPAgent

agent = AVPAgent.create(mock=True, name="my_agent")
agent.register(display_name="My Agent")
rep = agent.get_reputation(agent.did)
print(rep)
Connect to production server 
from agentveil import avp_tracked

@avp_tracked("https://agentveil.dev", name="my_agent", to_did="did:key:z6Mk...")
def review_code(pr_url: str) -> str:
    return analyze(pr_url)

>Pricing

Start free. Scale when you need to.

Community

Free

  • ✓ Unlimited agents
  • ✓ can_trust() advisory decisions
  • ✓ Full SDK + 12 MCP tools
  • ✓ 8 framework integrations
  • ✓ Offline verifiable credentials
  • ✓ Community support

pip install agentveil

Enterprise

Contact us

  • ✓ Everything in Community
  • ✓ Dedicated instance
  • ✓ Custom SLA
  • ✓ Audit log exports
  • ✓ Priority support
  • ✓ Custom deployment options

Contact Sales