Compliance Audit
Immutable audit trail for autonomous agent operations. Log skill executions, data access, decisions, and budget changes with tamper-evident hashes. Essential...
Description
name: compliance-audit description: Immutable audit trail for autonomous agent operations. Log skill executions, data access, decisions, and budget changes with tamper-evident hashes. Essential for enterprise governance, incident response, and trust verification. user-invocable: true metadata: {"openclaw": {"emoji": "📋", "os": ["darwin", "linux"], "requires": {"bins": ["python3"]}}}
Compliance Audit Trail
Immutable, tamper-evident audit logging for autonomous agents. Every action gets a hash-chained entry that can be verified for integrity.
Why This Exists
Autonomous agents make decisions, execute skills, access data, and spend money without human oversight. When something goes wrong, you need to know exactly what happened. Current agent frameworks have no standard audit trail — this fills that gap.
Commands
Log an action
python3 {baseDir}/scripts/audit.py log --action "skill_executed" --details '{"skill": "scanner", "target": "some-skill", "result": "clean"}'
Log a decision
python3 {baseDir}/scripts/audit.py log --action "decision" --details '{"choice": "deploy v2", "reason": "all tests passed", "alternatives_considered": ["rollback", "hotfix"]}'
Log data access
python3 {baseDir}/scripts/audit.py log --action "data_access" --details '{"resource": "api_key", "purpose": "moltbook_post", "accessor": "ghost_agent"}'
Log a budget change
python3 {baseDir}/scripts/audit.py log --action "budget_change" --details '{"amount": -10.00, "merchant": "namecheap", "reason": "domain purchase", "balance_after": 190.00}'
View recent entries
python3 {baseDir}/scripts/audit.py view --last 20
View entries by action type
python3 {baseDir}/scripts/audit.py view --action skill_executed
View entries in a time range
python3 {baseDir}/scripts/audit.py view --since "2026-02-15T00:00:00" --until "2026-02-16T00:00:00"
Verify audit trail integrity
python3 {baseDir}/scripts/audit.py verify
Export audit trail
python3 {baseDir}/scripts/audit.py export --format json > audit-export.json
python3 {baseDir}/scripts/audit.py export --format csv > audit-export.csv
Generate compliance summary
python3 {baseDir}/scripts/audit.py summary --period day
Entry Format
Each audit entry contains:
- timestamp — ISO 8601, UTC
- action — what happened (skill_executed, decision, data_access, budget_change, error, custom)
- agent — which agent performed the action
- details — structured JSON with action-specific data
- hash — SHA-256 hash chaining previous entry's hash + current entry (tamper-evident)
- sequence — monotonically increasing sequence number
Integrity Verification
The audit trail is hash-chained: each entry includes a SHA-256 hash of the previous entry's hash concatenated with the current entry's data. If any entry is modified or deleted, the chain breaks and verify will report the exact point of tampering.
Storage
Audit logs are stored in ~/.openclaw/audit/ as daily JSON files (audit-YYYY-MM-DD.json). This keeps individual files small while maintaining the full history.
Use Cases
- Incident response: What happened in the 5 minutes before the error?
- Budget accountability: Show every dollar spent and why
- Trust verification: Prove your agent hasn't been compromised
- Enterprise compliance: Meet audit requirements for autonomous systems
- Debugging: Trace the decision chain that led to an unexpected outcome
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