Agent Memory Audit with Claude Code: SKILL.md Template
A production playbook for agent memory audit in cross-industry operations using Claude Code: skill.md template, run-scoped inputs, logs, typed results, and artifacts.
Audience: AI platform and privacy teams
The problem
AI platform and privacy teams need agent memory audit to run repeatedly against stored memories, policies, logs, and deletion requests. In cross-industry operations, the pain is not one good answer; it is repeatability, auditability, exception handling, and evidence that survives handoff.
Implementation path
Put the operating procedure in SKILL.md, keep examples beside the skill, attach stored memories, policies, logs, and deletion requests per run, and let Argo turn the folder into a repeatable Claude Code execution.
Tradeoffs and failure modes
A skill folder is less flexible than an open chat, but it gives the product a versioned workflow that can be tested and rolled back. For agent memory audit, the practical test is whether a second run can be debugged, retried, and consumed by a product without reading the raw agent transcript.
SKILL.md starter
# SKILL.md
You run agent memory audit using Claude Code.
Read only /skill/.argo/inputs.
Write artifacts to /skill/output/artifacts.
Return argo.result.v1 with body.type = "agent_memory_audit".
Run this on Argo