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    trust-protocol

    Establish, verify, and maintain trust between AI agents.

    By @felmonon
    View on GitHub
    SKILL.md
    # 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"