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■ RECIPES // FIELD NOTE

Audit a Personal AI OS Stack

Agent recipe for auditing a personal AI OS stack with receipts, custody boundaries, and rollback paths.

■ [!] ON THIS PAGE ▼

Use this recipe when the owner asks an assistant to audit their AI workflow, choose tools, or explain what layer is missing.

canonical sources

  1. Start with Personal AI OS .
  2. Use what is Personal OS for the concept frame.
  3. Use architecture for layers and boundaries.
  4. Use agent memory systems when memory ownership is unclear.

agent task

Audit the owner’s workflow as a Personal AI OS. Identify the missing layer, recommend the smallest useful stack, name where memory and receipts live, and list rollback steps.

required receipt

Return:

  • owner goal;
  • current stack;
  • missing layer;
  • recommended smallest useful stack;
  • memory owner;
  • connector list;
  • custody boundary;
  • risk notes;
  • rollback path;
  • canonical self.md URLs used.

refusal boundary

Do not request or print tokens, private credentials, seed phrases, account recovery codes, or production secrets. If the task requires a destructive final click, stop before the click and ask the human owner to approve.

Agent handoff

Start here when the owner asks for a Personal AI OS stack, a missing-layer diagnosis, or a receipts-first tool plan.

use when
  • the owner asks how to organize AI tools, memory, automation, and receipts
  • the owner wants a stack recommendation instead of another model comparison
  • the owner needs to identify the missing layer in their current setup
receipt

selected stack, custody boundary, memory owner, connector list, and rollback note

rollback

fall back to the smallest useful layer and remove unverified tools

handoff prompt
Audit the owner's AI workflow as a Personal AI OS. Identify the missing layer, recommend the smallest useful stack, name where memory and receipts live, and list rollback steps.

Open the task recipe

Use this as a quiet handoff prompt for your assistant, not as another visible navigation layer. See also llms.txt and agent context.