qt-canvas2d

Use to generate or update Qt 6 CMake projects or edit CMakeLists.txt, add sources/resources or define targets (executable, QML module, library).

Generates standalone Markdown reference documentation for any Qt/C++ source files — Qt Widgets classes, Qt Quick backends, Qt/C++ modules, plain C++ utilities, structs, free-function headers, and entry points like main.cpp. Use this skill to document any .h or .cpp file: Qt classes, plain C++ code, utility helpers, or application startup files. Triggers on: "document this class", "write docs for my C++", "document main.cpp", "C++ API docs", "document my Qt app", or whenever C++ or header files are provided and documentation is needed. Works with single files, pasted code, or entire project folders. DO NOT use if the user asks for QDoc format output.

Invoke when the user asks to review, check, audit, or look over Qt6 C++ code — or suggest before committing. Runs deterministic linting (60+ rules) then deep-analysis agents (scaled to the size of the change) covering model contracts, ownership, threading, API correctness, error handling, and performance. Reports only high-confidence issues (>80/100) with structured mitigations. Read-only — never modifies code.

Extract component metadata from a Figma design system and generate production-ready QML controls. Use this skill whenever someone wants to turn Figma components into QML files — whether they say "generate components from Figma", "create QML controls based on a design system", "convert Figma components to QML", "build the component library", "extract button/input/checkbox from Figma", or anything similar. Requires design-tokens.json and QML design system singletons to already exist (from the token extraction skill). Uses Figma MCP to inspect components one at a time and maps variants, states, sizing, and token usage to idiomatic Qt Quick Controls 2 patterns. Trigger this skill at the component generation step of any QML design-system workflow.

Extract design tokens, text styles, and variables from a Figma design system and produce a design-tokens.json plus ready-to-use QML singletons. Use this skill whenever someone wants to pull their design system out of Figma — whether they say "export tokens from Figma", "get design tokens", "set up my design system", "read our Figma design system", "get Figma variables into QML", "pull our color palette from Figma", "import design tokens", "extract colors/typography/spacing from Figma", or similar. Trigger this skill at the start of any design-system workflow that involves a Figma source.

Generates standalone Markdown reference documentation for QML components and applications. Use this skill whenever you want to document QML files, create API reference docs for a QML component or module, document a Qt Quick application, or produce developer-facing documentation from .qml source code. Triggers on: "document this QML", "write docs for my QML", "create reference docs", "document QML component", "QML API docs", "document my Qt Quick component", "document my Qt app", or any time one or more .qml files are provided and documentation is needed. Works with single files, pasted code, or entire project folders. DO NOT use if the user asks for QDoc format output.

Use when the user is investigating QML / Qt Quick performance — both vague complaints ("the UI feels laggy", "this is slow", "frames are dropping", "the app stutters") and explicit asks to profile, find hotspots, or optimize bindings, signals, or rendering. Runs qmlprofiler on a 2D QML application, parses the .qtd trace, and analyzes hotspots against the source with frame-time, memory, and pixmap-cache summaries. Does NOT cover Qt Quick 3D.

Invoke when the user asks to review, check, audit, or look over Qt6 QML code -- or suggest before committing. Runs deterministic linting (48+ rules) then deep-analysis agents (scaled to the size of the change) covering bindings, layout, loaders, delegates, states, and performance. Optionally invokes system qmllint for type-level checks. Reports only high-confidence issues (>80/100) with structured mitigations. Read-only -- never modifies code.

Read first to make, edit, animate or render any video with HyperFrames (HTML rendered to video), including launch films, explainers, music videos, charts, maps, vertical clips, title cards, captions and overlays. Holds the render contract, the work loop and what each kind of video needs.

Get or make any media for a HyperFrames video - music, sound effects, images, icons, logos, voiceover, avatar and generated video, transcripts, cutouts, colour grades and looks - with HeyGen or free local tools, and mix placed audio. Also for footage that looks dark, flat or dull, or should be stylized or hidden.

Design mobile app screens with Sleek, edit Sleek projects, and implement their designs in React Native or HTML.

A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.

Generate AI videos with Google Veo, Seedance 2.0, HappyHorse, Wan, Grok and 40+ models via inference.sh CLI. Models: Veo 3.1, Veo 3, Seedance 2.0, HappyHorse 1.0, Wan 2.5, Grok Imagine Video, OmniHuman, Fabric, HunyuanVideo. Capabilities: text-to-video, image-to-video, reference-to-video, video editing, lipsync, avatar animation, video upscaling, foley sound. Use for: social media videos, marketing content, explainer videos, product demos, AI avatars. Triggers: video generation, ai video, text to video, image to video, veo, animate image, video from image, ai animation, video generator, generate video, t2v, i2v, ai video maker, create video with ai, runway alternative, pika alternative, sora alternative, kling alternative, seedance, happyhorse

Generate AI images with GPT-Image-2, FLUX, Gemini, Grok, Seedream, Reve and 50+ models via inference.sh CLI. Models: GPT-Image-2, FLUX Dev LoRA, FLUX.2 Klein LoRA, Gemini 3 Pro Image, Grok Imagine, Seedream 4.5, Reve, ImagineArt. Capabilities: text-to-image, image-to-image, inpainting, LoRA, image editing, upscaling, text rendering. Use for: AI art, product mockups, concept art, social media graphics, marketing visuals, illustrations. Triggers: flux, image generation, ai image, text to image, stable diffusion, generate image, ai art, midjourney alternative, dall-e alternative, text2img, t2i, image generator, ai picture, create image with ai, generative ai, ai illustration, grok image, gemini image, gpt image, openai image, chatgpt image

Create AI avatar and talking head videos via inference.sh CLI. Recommended: P-Video-Avatar (fastest, cheapest, built-in TTS). Also: OmniHuman, Fabric, PixVerse. Audio: Inworld TTS-2 (100+ languages, emotion steering for characters), ElevenLabs, Kokoro. Capabilities: audio-driven avatars, text-to-avatar, lipsync videos, talking head generation, virtual presenters, UGC content. Use for: AI presenters, explainer videos, virtual influencers, dubbing, marketing videos, UGC ads, gaming avatars, NPC dialogue. Triggers: ai avatar, talking head, lipsync, avatar video, virtual presenter, ai spokesperson, audio driven video, heygen alternative, synthesia alternative, talking avatar, lip sync, video avatar, ai presenter, digital human, ugc, ugc video, ugc ad, avatar ugc

Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.