> ## Documentation Index
> Fetch the complete documentation index at: https://xerg.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# QM limitations

> The explicit current coverage and certification boundaries for QM.

QM support is GA with explicit partial coverage. The adapter and `qm-snapshot/v1` format are platform-independent. The full transport acceptance matrix is certified against `xerg_export/v1` on Fly.io and QM commit `5eb3393315b45b338b860572ab516db9f6eae6da`.

Xerg does not claim complete QM model economics or provider-invoice reconciliation. QM currently omits some auxiliary model paths from its durable request ledger. An audit describes recorded observations, not every possible provider call.

Other boundaries:

* `run_activity` is pruned after approximately one hour. One-shot snapshots cannot reconstruct older tool history.
* Pi and OpenCode model `created_at` values are flush/capture times. Claude values are closer to result-step recording. Codex rows are turn aggregates.
* Retry attempts exist as run lifecycle evidence, but model spend is not attributable per attempt.
* Tool calls/results are not defensibly associated with model observations, so monetary `tool-loop` is disabled.
* Iteration counts and cache carryover are unavailable.
* `openrouter/auto` is unpriced without the actual routed response model.
* Continuous follow capture, polling watermarks, and interrupted-follow recovery are not currently supported.
* Local, Docker, AWS, external PostgreSQL, and other deployments can use snapshot mode or strict direct mode when their database supports a genuinely restricted role, but those platforms have not completed the Fly acceptance matrix.
* Fly Managed Postgres uses a disclosed operator-contained process boundary. It does not use Fly's broad managed reader and does not claim database-level least privilege.
* QM's current Fly Sprites backend resumes persistent Sprites without applying the configured sandbox OCI image. Offline private-Slack audit therefore requires an explicitly approved, version-verified Xerg CLI bootstrap inside that private Sprite; this limitation does not affect the core exporter or platform-independent adapter.
* A cold QM request to set up `https://xerg.ai/skill.md` can explain prerequisites, but it cannot grant database privileges, persist an admin skill pack, or provision secrets by itself.
* A QM Slack agent can audit only an authorized pre-created snapshot. It cannot start live database or Fly collection, and no live Slack-triggered bridge is currently supported.

Upstream proposals for routed response model, cost authority, and broader content-free telemetry are useful but do not block the current one-shot adapter.