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trust-protocol

Establish, verify, and maintain trust between AI agents.

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Installation

npx clawhub@latest install trust-protocol

View the full skill documentation and source below.

Documentation

Agent Trust Protocol (ATP)

Establish, verify, and maintain trust between AI agents. Bayesian trust scoring with domain-specific trust, revocation, forgetting curves, and a visual dashboard.

Install

git clone 
# No dependencies beyond Python 3.8+ stdlib
# Pair with skillsign for identity:

Quick Start

# Add an agent to your trust graph
python3 atp.py trust add alpha --fingerprint "abc123" --score 0.7

# Record interactions — trust evolves via Bayesian updates
python3 atp.py interact alpha positive --note "Delivered clean code"
python3 atp.py interact alpha positive --domain code --note "Tests passing"

# Check trust
python3 atp.py trust score alpha
python3 atp.py trust domains alpha

# View the full graph
python3 atp.py status
python3 atp.py graph export --format json

# Run the full-stack demo (identity → trust → dashboard)
python3 demo.py --serve

Commands

Trust Management

atp.py trust add <agent> --fingerprint <fp> [--domain <d>] [--score <0-1>]
atp.py trust list
atp.py trust score <agent>
atp.py trust remove <agent>
atp.py trust revoke <agent> [--reason <reason>]
atp.py trust restore <agent> [--score <0-1>]
atp.py trust domains <agent>

Interactions

atp.py interact <agent> <positive|negative> [--domain <d>] [--note <note>]

Challenge-Response

atp.py challenge create <agent>
atp.py challenge respond <challenge_file>
atp.py challenge verify <response_file>

Graph

atp.py graph show
atp.py graph path <from> <to>
atp.py graph export [--format json|dot]
atp.py status

Dashboard

python3 serve_dashboard.py          # localhost:8420
python3 demo.py --serve             # full demo + dashboard

Moltbook Integration

python3 moltbook_trust.py verify <agent>    # check agent trust via Moltbook profile

How Trust Works

  • Bayesian updates: Each interaction shifts trust scores with diminishing deltas (prevents thrashing)
  • Negativity bias: Negative interactions hit harder than positive ones boost
  • Domain-specific: Trust an agent for code but not for security advice
  • Forgetting curves: Trust decays without interaction (R = e^(-t/S))
  • Revocation: Immediate drop to floor, restorable at reduced score
  • Transitive trust: If you trust A and A trusts B, you partially trust B (with decay)

Integration with skillsign

ATP builds on [skillsign]() for identity:

  • Agents generate ed25519 keypairs with skillsign

  • Agents sign skills, others verify signatures

  • Verified agents get added to the ATP trust graph

  • Interactions update trust scores over time
  • Triggers

    "check trust", "trust score", "trust graph", "verify agent", "agent trust", "trust status", "who do I trust", "trust report"