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Limitations

The current release is an evidence-first alpha, not a production memory service. Treat these as design constraints, not fine print.

API and storage stability

  • API and on-disk schemas may change before 1.0.
  • Schema 2 has an explicit v0.1 → v0.2 migration plus verified backup/restore, but this is not a general downgrade or arbitrary-version migration framework.
  • The storage root must be dedicated to Citefold. Unrelated files in an uninitialized non-empty directory are rejected rather than adopted.
  • Candidate list/approve/reject exists in both Python and CLI paths; a bulk or graphical review workflow is not included.
  • Pin/unpin is available for active records; pinning only exempts decay and does not guarantee recall or prevent correction, archival, or deletion.

Language and extraction

  • Local text capture and recall are language-agnostic at the evidence level.
  • The built-in deterministic direct-write parser recognizes only a narrow set of explicit Chinese preference/reminder phrases.
  • Arbitrary semantic extraction needs supplied candidates or optional model consolidation.
  • Multi-Episode consolidation currently batches selected observations; entity/time/topic grouping and novelty/contradiction quality have not been independently evaluated.

Retrieval and budgets

  • The default path uses lexical matching and SQLite FTS5; optional embeddings are a secondary, rebuildable signal.
  • token_budget is a logical character proxy, not an exact provider token count.
  • LongMemEval retrieval is strong, but end-to-end QA is materially lower and uneven by question type.
  • Results have not been independently reproduced by a third party.

Multimodal quality

  • The offline benchmark uses supplied observations and does not measure OCR, ASR, vision, codec, or reader-LLM quality.
  • OpenRouter endpoint availability and ZDR routing can change.
  • Audio normalization and video extraction depend on external ffmpeg/ffprobe executables.
  • Video uses scene frames and a conservative short-clip fallback; it is not general video understanding.
  • Missing provider confidence is stored as 0.0, so such output will not silently become stable memory.

Security and privacy

  • Citefold has no authentication, remote authorization service, or application-level encryption at rest.
  • It is not a sandbox for malicious code in the same Python process.
  • JSONL ledgers are auditable but not cryptographically tamper-proof.
  • ZDR routing is not a compliance certification.
  • Hard deletion does not erase backups, exported logs, or external provider copies.

Operations and scale

  • Root shared/exclusive locking and scope/ledger serialization are designed for local POSIX process/thread coordination; network-filesystem semantics remain unverified.
  • Windows multi-process locking parity is not established.
  • v0.1 processes do not participate in the schema 2 root lock; they must be stopped before migration and must not be restarted against the migrated root.
  • Migration preflight, verified ZIP backup, additive recovery state, legacy concurrent-change preservation, and journaled restore are covered by local deterministic tests, including a store generated by v0.1.0 and key breaks before/after manifest commit and between directory swaps. This is not exhaustive crash injection, a real power-loss test, a production recovery drill, or proof across arbitrary filesystems.
  • restore --replace intentionally retains the prior root as a sensitive displaced_root; its sibling intent journal also makes the root parent operational state. Operator review, retention, and deletion are not automated.
  • Distributed replication, sharding, high availability, and multi-node consistency are not implemented.
  • There is no published scale, latency, storage-growth, or cost envelope yet.
  • SQLite and filesystem projections are appropriate for embedded use, not a claim of high-throughput service readiness.

Biological analogy

Citefold implements explicit episodes, consolidation, cues, reinforcement, decay, and forgetting. It does not reproduce emotional modulation, sleep-dependent consolidation, reconstructive recall, implicit memory, sensorimotor learning, or consciousness. “Human-memory-inspired” describes design prompts, not measured equivalence to the brain.

Evaluation gaps before 1.0

  • real users over weeks or months;
  • real OCR/ASR/video quality and error propagation;
  • adversarial media and prompt-injection evaluation beyond deterministic fixtures;
  • large-scale concurrency, exhaustive crash/power-loss injection beyond the covered deterministic breakpoints, and production recovery drills;
  • independent security/threat-model review;
  • migration compatibility beyond the checked-in v0.1 → v0.2 fixture and with real deployment histories;
  • third-party benchmark reproduction.

If any of these are hard requirements, treat Citefold as a component to evaluate—not a finished solution.