Semantic recall in · per-record admission decisions out

Recalled memory is handled as material, not as instructions.

Memory Firewall takes a whole semantic recall set, presses each candidate through one canonical resolver, and shows which records may enter the working context — before anything reaches an action boundary.

  • 4routes one candidate set can take
  • 10committed terminal receipt rows
Open the containment workbench

Containment workbench

Build a candidate set, choose the task scope, and add one grounded operator note. Every control here changes the records that are actually sent to the resolver.

1 · Prompt and context

Recall preset
Candidate set (2 of 6 records)
Task scope

Your text is wrapped as one extra typed record (operator-note@live, entity operator_note) and scanned by the same resolver. Imperatives such as run command or credential-shaped strings change its disposition; it never overrides the fixture records’ own outcomes.

2 · Canonical evaluation

Loading the first candidate set…

3 · Trace

  1. Recall integrityAn empty candidate set stays unknown; it is never read as an absence of history.
  2. Recursive taint scanEvery nested string is inspected for imperatives, overrides and credential shapes.
  3. Schema validationTyped fields, unique IDs and parseable dates are required, never repaired by a model.
  4. Lifecycle resolutionID-based supersession, revocation and expiry run before any scope filtering.
  5. Scope and provenanceOnly current, in-scope, grounded records survive; a cross-scope successor never revives its predecessor.
  6. Action boundaryAdmitted memory is data. Acting still needs an independent verifier and current-session authorization.

Resolver on this bench: web/lib/firewall-core.mjs

4 · Reproduce in the CLI

The same candidate set resolves identically outside the browser.

make web-parity       # the browser and the Python resolver must agree, record for record
make synthetic-stand  # replays the pinned candidate-set corpus in isolation

Exact call for the set currently on the bench:

Run an evaluation to render the matching CLI call.

5 · Receipt cabinet

This workbench sorts a candidate set and explains its dispositions. The archived receipt record is a separate artefact, so a browser result is never mistaken for a storage operation.

  • evidence/mainnet-receipts.jsonBlob-identifier receipt entries, checked by scripts/check_evidence.py.
  • evidence/MAINNET_EVIDENCE.mdThe terminal capture procedure and its cold-client verification steps.
  • Workbench resultEach result names the candidate, disposition, and rule that produced it.