Dxpert.ai — industrial AI Readiness & UNS agents vs Orcaslicer MCP

get_slice_warnings

Just the warnings/errors from the last (or current) slice, plus validity - the fast 'did anything go wrong' check and the way to confirm a fix cleared. NOTE: only as complete as the API exposes. On the current fork build this may report valid with an empty warnings list even when the GUI shows a plate-boundary toast - the fork must populate the plater warning list (tracked as the fork batch). Once it does, this reports the real warnings with no change here.

get_slice_breakdown

Per-feature breakdown of the last slice + a stateless predicted-vs-observed flow check. Returns per-role time/filament + speed/flow ranges, global time-weighted metric distributions, per-layer aggregates, and a prediction_check flagging where the profile's speed was silently throttled at the flow ceiling ('clamped'). Answers 'which feature is the time hog' directly instead of by trial slicing. Degrades to {"available": false, "reason": ...} on fork builds that don't emit the breakdown, or when there is no valid slice.

cancel_slice

Abort a running slice, or unwedge a stale 'slicing' state (e.g. after an object outside the bed). Safe when idle.

slice_and_wait

Slice the current plate and block until it finishes, then return the final stats and warnings in one call. If the plate is already sliced and unchanged, it returns the existing result without re-slicing. This is the usual way to slice when you want the outcome immediately. For a non-blocking start, use slice then poll get_slice_status; to sweep one setting across values, use compare_settings.

apply_and_slice

Apply config overrides and then slice in one step, returning {applied, errors, result} with the resulting stats and warnings. The changes are atomic (any invalid key rejects the whole batch) and unsaved, exactly like set_config, so they revert if the preset is reselected. Use this to test the effect of a tweak in a single call. Use set_config then slice_and_wait to keep the steps separate, or compare_settings to try several values of one key.

compare_settings

For each value of `key`, slice and collect stats/warnings; restore the original when done. Non-destructive: the original value of `key` is put back even on error.

compare_slices

Slice the current plate under several named variants and compare the cost of each. Each variant is {"name": str, "changes": {setting: value}}; changes={} means the current config as-is (a natural baseline row). Applies each variant over the ORIGINAL config (resetting between variants, so they don't stack), slices it, then restores your config exactly as it was - nothing is left changed (slice validity is left false, as after any un-resliced edit). Returns a ready-to-relay `headline` and `table_markdown`, plus structured `variants`. All deltas and percentages are ALREADY computed and rounded against `baseline` (defaults to the changes={} variant, else the first) - relay them as given rather than recomputing. `recommended` names one pick; `recommended_is_dominant` says whether it beats every variant on every axis (time, filament, warnings) or is only the fastest warning-free option amid a genuine trade-off (`tradeoff` then names the frontier). Each variant is a full slice (minutes); capped at 8. Set detail=True only when a per-feature (wall/infill/support) split is wanted - it grows the response ~N x. With more than ~5 variants, lead with the recommendation and the extremes, not all rows.