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Governance behavior for AI agents governed by DashClaw. Teaches the governance protocol: when to call guard (risk thresholds), how to interpret decisions (allow/warn/block/require_approval), when to record actions, how to wait for approvals, and session lifecycle management. Loads org-specific policies and capabilities from MCP resources at session start. Use with @dashclaw/mcp-server. Trigger on: governed agent, dashclaw governance, guard policy, approval wait, governed capability, risk threshold, action recording, session lifecycle.
Related occupations SOC
Based on SOC occupation classification
name create-policies description Create and test DashClaw guard policies for agent governance license MIT metadata {"author":"ucsandman","version":"1.0.0","category":"configuration"}
Create Guard Policies
Help developers define, import, and test guard policies that control what agents can and cannot do.
Policy Types
Type Purpose Example risk_thresholdBlock/warn when risk score exceeds limit Block actions with risk > 80 action_type_restrictionAllow/deny specific action types Block security actions without approval approval_gateRequire human approval for matching actions Require approval for deploys webhook_checkCall external endpoint for policy decision Check Jira ticket status before deploy semantic_guardrailLLM-based content analysis Block PII in action metadata
Guard Modes
off — No policy enforcement (development only)
warn — Log policy violations but allow execution
enforce — Block policy violations (production recommended)
Defining Policies in YAML
Risk Threshold Policy name: high-risk-blocker
type: risk_threshold
mode: enforce
conditions:
risk_score_min: 80
reversible: false
action: block
reason: "Irreversible actions with risk >= 80 require manual execution"
Action Type Restriction name: no -unattended-deploys
type: action_type_restriction
mode: enforce
conditions:
action_types:
- deploy
- database
action: require_approval
reason: "Deploy and database actions require human approval"
Approval Gate name: production-approval-gate
type: approval_gate
mode: enforce
conditions:
systems_touched:
- production
risk_score_min: 50
action: require_approval
reason: "Production access with risk >= 50 requires approval"
Cost Ceiling name: cost-ceiling
type: risk_threshold
mode: enforce
conditions:
cost_estimate_max: 100.00
action: block
reason: "Actions exceeding $100 estimated cost are blocked"
Content Filter name: no -secrets-in-metadata
type: semantic_guardrail
mode: enforce
conditions:
scan_fields:
- declared_goal
- output_summary
patterns:
- "password"
- "api_key"
- "secret"
action: block
reason: "Sensitive data detected in action metadata"
Importing Policies
Via API
const response = await fetch (`${baseUrl} /api/policies` , {
method : 'POST' ,
headers : {
'Content-Type' : 'application/json' ,
'x-api-key' : process.env .DASHCLAW_API_KEY
},
body : JSON .stringify ({
name : 'high-risk-blocker' ,
type : 'risk_threshold' ,
mode : 'enforce' ,
conditions : { risk_score_min : 80 , reversible : false },
action : 'block' ,
reason : 'Irreversible high-risk actions are blocked'
})
});
Via Legacy SDK Policy Packs import { DashClaw } from 'dashclaw/legacy' ;
const claw = new DashClaw ({ baseUrl, apiKey, agentId });
await claw.importPolicies ({ pack : 'enterprise-strict' });
Testing Policies
Test a Single Policy
const result = await fetch (`${baseUrl} /api/policies/test` , {
method : 'POST' ,
headers : {
'Content-Type' : 'application/json' ,
'x-api-key' : process.env .DASHCLAW_API_KEY
},
body : JSON .stringify ({
action_type : 'deploy' ,
risk_score : 85 ,
reversible : false ,
systems_touched : ['production' ]
})
});
Test All Policies (Legacy SDK) const results = await claw.testPolicies ();
Generate Proof Report const report = await claw.getProofReport ({ format : 'md' });
Common Policy Patterns
Development Environment
- name: dev-risk-warning
type: risk_threshold
mode: warn
conditions: { risk_score_min: 50 }
action: warn
reason: "High risk action detected (dev mode — not blocked)"
Production Environment
- name: prod-risk-gate
type: risk_threshold
mode: enforce
conditions: { risk_score_min: 70 }
action: require_approval
- name: prod-deploy-gate
type: action_type_restriction
mode: enforce
conditions: { action_types: [deploy , database , security ] }
action: require_approval
- name: prod-irreversible-block
type: risk_threshold
mode: enforce
conditions: { risk_score_min: 90 , reversible: false }
action: block
Scoping Policies Policies can be scoped to specific agents or apply org-wide:
{
"name" : "deploy-agent-only" ,
"agent_id" : "deploy-agent-1" ,
"type" : "approval_gate" ,
"conditions" : { "action_types" : [ "deploy" ] } ,
"action" : "require_approval"
}
If agent_id is omitted, the policy applies to all agents in the org.
Listing Active Policies
curl -H "x-api-key: $DASHCLAW_API_KEY " $DASHCLAW_BASE_URL /api/policies
Response includes all active policies with their type, mode, conditions, and scope.