Audit Log Investigation with Claude Code: Result JSON Schema

A production playbook for audit log investigation in cross-industry operations using Claude Code: result json schema, run-scoped inputs, logs, typed results, and artifacts.

Audience: Security operations teams

The problem

Security operations teams need audit log investigation to run repeatedly against audit logs, entity metadata, and escalation policy. In cross-industry operations, the pain is not one good answer; it is repeatability, auditability, exception handling, and evidence that survives handoff.

Implementation path

Define the outer result contract once, let the audit log investigation skill own body.data, and reject terminal output that does not match the expected schema.

Tradeoffs and failure modes

Schema enforcement adds upfront design work, but removes prompt parsing from the product surface. For audit log investigation, the practical test is whether a second run can be debugged, retried, and consumed by a product without reading the raw agent transcript.

Result shape

{
  "schema_version": "argo.result.v1",
  "summary": "audit log investigation completed",
  "body": { "type": "audit_log_investigation", "data": {}, "exceptions": [] },
  "artifacts": []
}

Run this on Argo