- Ignore undefined values before cache invalidation and preview mutation\n- Treat text direction as a glyph-shaping input\n- Cover the corrected invalidation contract
Keep authoritative derived glyphs through layout, alignment, fill, and decoration changes while still invalidating them for actual shaping edits.
Add scene-graph invalidation coverage and a Gold Preview fixture regression test.
Co-authored-by: Joseph Cumines <joeycumines@gmail.com>
- Warn once with the rejected surface dimensions and original CanvasKit error
- Disable repeated cache allocation attempts until the renderer surface is replaced
- Keep direct scene rendering as the visible fallback
- Scale retained margins to a fixed device-pixel budget on large viewports
- Fall back to direct scene rendering when CanvasKit rejects an offscreen surface
- Cover the reported wide HiDPI geometry without coupling rendering to a WebGL context
- Traverse fixed wrappers only to reach descendants with SCALE constraints
- Preserve fixed siblings and use component geometry as the scale basis
- Cover target-aspect icons without changing the Preline geometry baseline
- Use preserved targetAspectRatio metadata as the instance scale basis
- Scale nested geometry through fixed wrapper layers
- Cover proportion-constrained logo imports with a regression test
- Scope recipes to OpenAI-compatible endpoints and enforce CORS status and header values
- Record unavailable ID coverage, output budgets, stream HTTP status, finish reasons, and zero-call failures
- Repair the repository README link to the published compatibility reference
- Recompute Yoga positions after shaped text changes effective geometry
- Resolve inherited stretch and skip hidden or absolute children
- Share and normalize Plugin API transform matrices
- Centralize design-profile eligibility for the selector, role assignment, fallback, and tests
- Keep built-in provider model selection intact while switching saved custom profiles
- Add localized accessible labeling and constrain long profile names
The chat model chip is a dropdown for built-in providers but a static label
for OpenAI-compatible and custom-model setups, so anyone using a custom
endpoint had to open Settings to change models -- even with several models
already configured.
Add a profile switcher that reassigns the design role from the chat panel.
It lists saved profiles that can use tools, shows the profile name rather
than the raw model ID, and badges the vision-capable ones. It writes the
same assignments.design field the Settings dropdown does, so the two stay in
sync.
Only renders when more than one tools-capable profile exists; a single
profile keeps the existing label. Built-in providers keep ProviderModelSelect
unchanged.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
- Return rotation and reflection matrices for relative and absolute transforms
- Preserve authoritative imported FIG transforms until geometry is edited
- Cover nested rotation and reflected vector behavior
- Reconcile stale generated text widths with CanvasKit measurements
- Propagate effective widths through HUG containers while preserving fixed geometry
- Cover component-lineage and stretched-text safeguards
- Publish the compatibility reference in the VitePress site and link localized AI guides to the canonical English page
- Correct current Anthropic and credential-storage behavior
- Make CORS, streaming, pricing, context, and reasoning measurements reproducible and security-safe
The probe behind this page used max_tokens 2000, which starves reasoning
models: they spend the whole budget thinking and emit no tool calls, with
finish_reason length and no error. That looks identical to a model that
cannot call tools, and two models were wrongly marked "avoid" because of it.
Re-ran every Scaleway model at 16384. All five are clean -- qwen3.6-35b-a3b
goes from 1/3 to 3/3, mistral-small-3.2-24b from 2/3 to 3/3. Tool calling no
longer separates them, so the recommendation now follows price, vision and
context: mistral-small-3.2-24b is cheapest with vision, gemma-4-26b-a4b-it
for double the context.
Document the failure mode, the reasoning_effort lever (only "none" had any
effect on Scaleway; "low" did nothing), and ask contributors to record the
token budget alongside results. Nebius and TensorX rows are marked as
measured at 2000 so they are not read as comparable.
Refs #454
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Add measured Vision and context-window columns alongside the tool-calling
metrics, and four more Scaleway models. gemma-4-26b-a4b-it becomes the
recommendation: the only model tested that is clean on cost, tool calling
and vision at once, with 2x the context of gpt-oss-120b.
Document models.dev as a prefill source for new rows, with the caveat that
it describes nominal capabilities rather than deployment behaviour. It was
wrong on two of seven models checked here -- it marks scaleway/gpt-oss-120b
as vision-capable when the model refuses images, marks
scaleway/mistral-small-3.2-24b as text-only when it reads them, and reports
tool_call: true for models that emit no tool calls in practice.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
TensorX was marked browser-broken based on unauthenticated probes. With a
valid key it returns Access-Control-Allow-Origin on 200 responses; only
errors (401/403/500) omit it. Downgrade to a warning and document the
methodology error, since an unauthenticated probe cannot distinguish a
gateway-rejected error from a genuinely broken provider.
Scaleway behaves the same way and is added with the same caveat.
Add four Scaleway model results. gpt-oss-120b streams cleanly there
(0 violations / 135 deltas) despite misrouting on Nebius, so the vLLM
tool-call bug is a deployment issue rather than a model one, and the
client-side shim is avoidable by switching provider. That makes
gpt-oss-120b the cost-effective recommendation at EUR 0.15/0.60.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
The table ranked models on tool-calling correctness alone, which recommended
Kimi-K3 at $3/$15 per 1M tokens. The chat panel runs up to 50 agent steps and
resends tool schemas each step, so price compounds and that was the wrong
default.
Add a cost column, move the recommendation to Kimi-K2.7-Code (same clean
behaviour, ~1/4 the price), and note that gpt-oss-120b is ~25x cheaper than
K3 and would be the obvious default once the vLLM shim exists.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Whether a provider works in the web build depends on CORS headers being set
on the response (not just the preflight), and whether a model is usable in
the AI chat panel depends on its streaming tool calls being well-formed.
Neither is documented by providers, so record what has been measured.
Covers 11 providers and 5 models, each row dated. Documents two recurring
failure modes: vLLM misrouting the final tool-call argument chunk to
index + 1 without an id, and reasoning models returning null content under
the connection test's maxOutputTokens: 1.
Includes copy-paste curl recipes so others can add rows.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
- Preserve Figma min/max constraints, scalar variable bindings, and direct text bounds
- Reflow only authoritative generated instance geometry and pinned descendants
- Avoid double-applying auto spacing and unsafe lone-child normalization
- Replace the full-width editor header action with a shared browser and native menu command
- Localize the destination and cover menu schema and browser navigation
Once a document is opened from the storage workspace there is no way back
to it: the only in-app route is Settings -> Cloud storage -> Open workspace,
and the desktop shell has no browser back at all.
Add an explicit button in the shared header row (rendered on both web and
Tauri, unlike the File/Edit menubar below it) that routes to /storage. It is
a fixed destination rather than history navigation, so it behaves the same
on both platforms.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
- Reframe entries around user-visible outcomes and consolidate related changes
- Document missing features, fixes, performance improvements, and SDK migrations
- Support vectorPaths, vectorNetwork, and async network assignment
- Normalize geometry bounds and preserve winding and region paint semantics
- Validate network topology and expose handle mirroring only on vectors
Co-authored-by: Rob Coenen <753704+rcoenen@users.noreply.github.com>
- Include stroke color and rounded weight in node and child summaries
- Select the first visible stroke when hidden paints precede it
- Cover both describe output paths with mixed stroke visibility
Co-authored-by: Rob Coenen <753704+rcoenen@users.noreply.github.com>
- Validate inline SVG roots against their supported root props
- Leave descendant SVG markup to the SVG renderer instead of Design JSX validation
- Keep warnings for unsupported root props and cover both paths
Co-authored-by: Rob Coenen <753704+rcoenen@users.noreply.github.com>
- Name every create_shape node type in the tool description
- Direct arbitrary geometry requests to SVG-backed create_vector input
- Keep the prose synchronized with the declared type enum
Co-authored-by: Rob Coenen <753704+rcoenen@users.noreply.github.com>
- Normalize SVG paint sentinels before creating icon vector nodes
- Keep inline outline artwork transparent instead of falling back to black
- Cover fill and stroke none values through the Design JSX renderer
Co-authored-by: Rob Coenen <753704+rcoenen@users.noreply.github.com>
