Audit Logging

The compliance backbone — every agent action gets a log entry, every significant decision gets a record.

Standards alignment

Audit event format

Each log entry is one JSON object per line, appended to .compliance/audit.log. Full schema: skills/audit-logging/audit-event.schema.json.

Required fields

{
  "event_id": "uuid-v4",
  "timestamp": "ISO 8601",
  "trace_id": "hex-32",
  "event_class": "tool_call | decision | data_access | error",
  "activity": "read | write | classify | scan | block | approve",
  "severity": "INFO | LOW | MEDIUM | HIGH | CRITICAL",
  "outcome": "success | failure | blocked | deferred",
  "summary": "Human-readable one-liner"
}

Optional fields

Add only when relevant — keep log entries lean:

Agent Decision Record (ADR)

An audit event with event_class: "decision" and a decision block. Created when the agent:

• Blocks or allows a RESTRICTED data operation
• Answers a gap analysis question autonomously
• Encounters conflicting information
• Invokes external tools with security implications

Decision block

"decision": {
  "action": "block | approve | defer",
  "reasoning": "Why this action was taken",
  "policy_ref": "GDPR Art. 9 | NIS2 Art. 21(2)(h) | ...",
  "human_override": false
}

Storage

• Location: .compliance/audit.log (project root)
• Format: append-only, one JSON object per line
• Rotation: optional daily files (audit-YYYY-MM-DD.log)
• Integrity: UUID per event, sequence breaks detectable
• Central collection: Push to cloud storage via the compliance-hub skill

Retention guidance

Logging in AI-generated code

When writing code, include structured logging for: auth events, authorization, data access, data modification, external API calls, errors, config changes, batch jobs. Use structured key-value pairs — never string interpolation. Never log secrets, PII, or session tokens.

For the full operations table, correct/wrong code examples per language, what-not-to-log rules, and language-specific logger recommendations, see references/logging-guide.md.

Agent instructions

Follow this process every session:

1. Session start — generate a trace_id (32-char hex). Use it for all events in this session.
2. Per step — generate a span_id (16-char hex) for each discrete operation.
3. Before tool execution — log a tool_call event with the tool name.
4. After tool execution — update with outcome and exit code.
5. On any decision involving classified data — create an ADR with the decision block.
6. Append each event as a single JSON line to .compliance/audit.log.
7. PROACTIVE — when writing code: Whenever you generate, write, or modify source code, you MUST include proper structured audit logging following the rules above. This is not optional. Specifically:

• Add logging imports/setup if the file doesn't have them
• Add structured log statements for every operation listed in the mandatory logging table
• Use the correct structured format for the language (no string interpolation)
• Include correlation IDs (trace_id, request_id) where the framework supports it
• NEVER log sensitive data — follow the "what MUST NOT be logged" table
• When modifying existing code, add logging to any new or changed code paths

1. When reviewing AI-generated code: Check that all operations have structured logging. Flag missing logging as a compliance gap.

Example log entry

{"event_id":"a1b2c3d4-...","timestamp":"2026-03-13T10:15:00Z","trace_id":"abc123...","event_class":"tool_call","activity":"scan","severity":"INFO","outcome":"success","summary":"Scanned src/ for sensitive data patterns","tool":{"name":"data-sensitivity","exit_code":0}}

Example ADR

{"event_id":"e5f6g7h8-...","timestamp":"2026-03-13T10:15:05Z","trace_id":"abc123...","event_class":"decision","activity":"block","severity":"HIGH","outcome":"blocked","summary":"Blocked commit containing BSN","resource":{"type":"file","id":"src/users.py","classification":"RESTRICTED"},"decision":{"action":"block","reasoning":"File contains plaintext BSN (national ID)","policy_ref":"GDPR Art. 87","human_override":false}}