AgentMesh Governance — Trust & Policy for OpenClaw Agents

Zero-trust governance layer for OpenClaw agents. Enforce policies, verify identities, score trust, and maintain tamper-evident audit logs — all from your agent's command line.

Setup

Install the AgentMesh governance CLI:

pip install agentmesh-governance

If agentmesh-governance is not yet on PyPI, install directly from source:

pip install "agentmesh @ git+https://github.com/imran-siddique/agent-mesh.git"

Scripts

All scripts are in scripts/. They wrap the governance engine and output JSON results.

Check Policy Compliance

Evaluate an action against a governance policy before execution:

scripts/check-policy.sh --action "web_search" --tokens 1500 --policy policy.yaml

Returns JSON with allowed: true/false, any violations, and recommendations. Use this before executing any tool call to enforce limits.

Get Trust Score

Check an agent's current trust score (0.0 – 1.0):

scripts/trust-score.sh --agent "research-agent"

Returns the composite trust score with breakdown across 5 dimensions: policy compliance, resource efficiency, output quality, security posture, collaboration health.

Verify Agent Identity

Verify an agent's Ed25519 cryptographic identity before trusting its output:

scripts/verify-identity.sh --did "did:agentmesh:abc123" --message "hello" --signature "base64sig"

Returns verified: true/false. Use when receiving data from another agent.

Record Interaction

Update trust scores after collaborating with another agent:

scripts/record-interaction.sh --agent "writer-agent" --outcome success
scripts/record-interaction.sh --agent "writer-agent" --outcome failure --severity 0.1

Success adds +0.01 to trust score. Failure subtracts the severity value. Agents dropping below the minimum threshold (default 0.5) are auto-blocked.

Audit Log

View tamper-evident audit trail with Merkle chain verification:

scripts/audit-log.sh --last 20
scripts/audit-log.sh --agent "research-agent" --verify

The --verify flag checks Merkle chain integrity — any tampering is detected.

Generate Identity

Create a new Ed25519 cryptographic identity (DID) for your agent:

scripts/generate-identity.sh --name "my-agent" --capabilities "search,summarize,write"

Returns your agent's DID, public key, and capability manifest.

Policy File Format

Create a policy.yaml to define governance rules:

name: production-policy
max_tokens: 4096
max_tool_calls: 10
allowed_tools:
  - web_search
  - file_read
  - summarize
blocked_tools:
  - shell_exec
  - file_delete
blocked_patterns:
  - "rm -rf"
  - "DROP TABLE"
  - "BEGIN CERTIFICATE"
confidence_threshold: 0.7
require_human_approval: false

When to Use This Skill

• Before tool execution: Run check-policy.sh to enforce limits
• Before trusting another agent's output: Run verify-identity.sh
• After collaboration: Run record-interaction.sh to update trust
• Before delegation: Check trust-score.sh — don't delegate to agents below 0.5
• For compliance: Run audit-log.sh --verify to prove execution integrity
• On setup: Run generate-identity.sh to create your agent's DID

What It Enforces

Architecture

This skill bridges the OpenClaw agent runtime with the AgentMesh governance engine:

OpenClaw Agent → SKILL.md scripts → AgentMesh Engine
                                     ├── GovernancePolicy (enforcement)
                                     ├── TrustEngine (5-dimension scoring)
                                     ├── AgentIdentity (Ed25519 DIDs)
                                     └── MerkleAuditChain (tamper-evident logs)

Part of the Agent Ecosystem: AgentMesh · Agent OS · Agent SRE