Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
AgentMesh Governance adds a zero-trust layer to OpenClaw agents, enforcing token limits, tool allowlists/blocklists, and content policies before execution. Agents get Ed25519 cryptographic identities (DIDs) and trust scores across five dimensions. All actions are recorded in tamper-evident Merkle chain audit logs.
Unlike ad-hoc prompt-based restrictions, this enforces governance cryptographically and tracks trust scores over time, making it auditable and tamper-evident rather than easily bypassed.
When to use it
- Blocking a research agent from running shell commands via policy file
- Verifying another agent's DID before accepting its summarized output
- Checking trust score before delegating a subtask to a writer agent
- Proving execution integrity to a compliance team with Merkle-verified audit logs
- Auto-blocking agents that repeatedly fail collaborative interactions
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: enforce policy on a web_search action with 1500 tokens before executing
- 1Run check-policy.sh with --action web_search --tokens 1500 --policy policy.yaml
- 2Governance engine evaluates action against max_tokens, allowed_tools, and blocked_patterns
- 3Returns JSON with allowed: true/false and any violations
- 4If allowed, proceed with tool execution
- 5Run record-interaction.sh after completion to update trust score
JSON response: {"allowed": true, "violations": [], "recommendations": []}