FigJam plugin development workflow. Use when modifying code.ts (canvas rendering), ui.ts (WebSocket/UI), fixing plugin build errors, or adding new rendering features.
npx skills add https://github.com/aiskillstore/marketplace --skill figjam-plugin
| Thread | File | APIs | Role |
|--------|------|------|------|
| Main | code.ts | figma.* only | Canvas rendering |
| UI | ui.ts | Browser APIs | WebSocket client, connection UI |
Critical: code.ts has NO browser APIs (window, document, fetch, WebSocket).
CLI ←─ WebSocket ─→ ui.ts ←─ postMessage ─→ code.ts ←─ figma.* ─→ Canvas
cd packages/plugin && bun run build
Import: Figma Desktop → Plugins → Development → Import from manifest → packages/plugin/manifest.json
@figram/core, normalizes to IR| File | Purpose |
|------|---------|
| manifest.json | Plugin config |
| src/code.ts | Canvas rendering |
| src/ui.ts | WebSocket + UI |
| src/icons/ | Service icons |
Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.
Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.
Best practices for Remotion - Video creation in React
Generate AI-powered podcast-style audio narratives using Azure OpenAI's GPT Realtime Mini model via WebSocket. Use when building text-to-speech features, audio narrative generation, podcast creation from content, or integrating with Azure OpenAI Realtime API for real audio output. Covers full-stack implementation from React frontend to Python FastAPI backend with WebSocket streaming.
Best practices for Remotion - Video creation in React
Use this skill when building applications with Gemini API hosted models, including Gemini and Gemma 4, working with multimodal content (text, images, audio, video), implementing function calling, using structured outputs, or needing current model specifications. Covers SDK usage...
Turn error logs, screenshots, voice notes, and rough bug reports into crisp, developer-ready GitHub issues with repro steps, impact, and evidence.
Python library for single-particle tracking (SPT) in video microscopy via the Crocker-Grier algorithm. Locate particles (fluorescent spots, colloids, vesicles, cells) per frame, link into trajectories, filter short tracks, and compute MSD for diffusion analysis. 2D/3D with subpixel accuracy; reads TIF stacks, AVI, image series via pims. Use for quantitative SPT and diffusion coefficient extraction from fluorescence or brightfield video.
Take aiskillstore/figjam-plugin from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.