Review what was extracted
The scan produces a proposal. Nothing is canonical yet. This is the step where you decide what your memory layer remembers.
Open the dashboard
From your repo root:
preset open
The command opens the review dashboard in your browser with your scan loaded. You'll see three tabs, Tokens, Patterns, and Proposals, with a count and an average confidence score at the top of each.
The dashboard is a private, per-repo view. Nothing is published until you explicitly promote it.
Three actions per artifact
Every extracted item has the same three actions:
- Confirm: accept as-is. The artifact enters the memory layer with the name and shape the scanner inferred.
- Edit: adjust the name, description, or fields. Useful when the scanner's name is technically correct but doesn't match how your team talks about it.
- Reject: remove from the proposal. Rejected items are tracked so re-scanning doesn't re-propose them.
Confidence scores guide your attention. High-confidence items are usually correct; you'll mostly skim and confirm. Medium and low-confidence items deserve a closer look: those are where the scanner saw a recurring shape but isn't sure what to call it.
Edit freely. The AI tools that consume your memory layer will read the names and descriptions you chose here. An agent asked to build a "primary action" is more likely to match a preset you named primary-action than one called btn_submit_v2.
Identity is assigned here
When you confirm an artifact, preset AI mints a stable identity: independent of the name. If you rename the preset later, agents still resolve correctly because the identity tracks through the rename.
This is the move that makes rename-safe refactors possible. Your team can evolve the vocabulary; the memory layer preserves the continuity.
What you reject is also recorded. Drift detection uses that record: if you rejected a pattern once and the scanner re-proposes it after new code lands, preset AI can flag the regression rather than silently re-suggesting.