Establish, verify, and maintain trust between AI agents. Bayesian trust scoring with domain-specific trust, revocation, forgetting curves, and a visual dashboard.
Scanned 9/7/2026
Install to Claude Code
npx -y skills add Demerzels-lab/elsamultiskillagent --skill trust-protocol --agent claude-codeInstalls into .claude/skills of the current project.
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# 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
```bash
git clone https://github.com/FELMONON/trust-protocol.git
# No dependencies beyond Python 3.8+ stdlib
# Pair with skillsign for identity: https://github.com/FELMONON/skillsign
```
## Quick Start
```bash
# 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
```bash
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
```bash
atp.py interact <agent> <positive|negative> [--domain <d>] [--note <note>]
```
### Challenge-Response
```bash
atp.py challenge create <agent>
atp.py challenge respond <challenge_file>
atp.py challenge verify <response_file>
```
### Graph
```bash
atp.py graph show
atp.py graph path <from> <to>
atp.py graph export [--format json|dot]
atp.py status
```
### Dashboard
```bash
python3 serve_dashboard.py # localhost:8420
python3 demo.py --serve # full demo + dashboard
```
### Moltbook Integration
```bash
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](https://github.com/FELMONON/skillsign) for identity:
1. Agents generate ed25519 keypairs with skillsign
2. Agents sign skills, others verify signatures
3. Verified agents get added to the ATP trust graph
4. 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"
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