remarkable
Fetch handwritten notes, sketches, and drawings from a reMarkable tablet via Cloud API (rmapi). Process content by refining artwork with AI image generation, extracting handwritten text to memory/journal, or using sketches as input for other workflows. Use when working with reMarkable tablet content, syncing handwritten notes, processing sketches, or integrating tablet drawings into projects.
What this skill does
# reMarkable Tablet Integration (rmapi)
Fetch handwritten notes, sketches, and drawings from a reMarkable tablet via Cloud API. Process them — refine artwork with AI image generation, extract text to memory/journal, or use as input for other workflows.
## Typical Use Cases
1. **Journal entries** — User writes thoughts on reMarkable → fetch → OCR/interpret → append to `memory/YYYY-MM-DD.md` or a dedicated journal file
2. **Sketch refinement** — User draws a rough graphic → fetch → enhance with nano-banana-pro (AI image editing) → return polished version
3. **Brainstorming/notes** — User jots down ideas, lists, diagrams → fetch → extract structure → add to project docs or memory
4. **Illustrations** — User creates hand-drawn art → fetch → optionally stylize → use in blog posts, social media, etc.
## Processing Pipeline
```
reMarkable tablet → Cloud sync → rmapi fetch → PDF/PNG
↓
┌─────────────┴─────────────┐
│ │
Text content? Visual/sketch?
│ │
OCR / interpret nano-banana-pro
│ (AI enhance)
│ │
Add to memory/ Return refined
journal/project image to user
```
## Setup
- **Tool:** rmapi (ddvk fork) v0.0.32
- **Binary:** `~/bin/rmapi`
- **Config:** `~/.rmapi` (device token after auth)
- **Sync folder:** `~/clawd/remarkable-sync/`
### Authentication (ONE-TIME)
1. User goes to https://my.remarkable.com/connect/desktop
2. Logs in, gets 8-character code
3. Run `rmapi` and enter the code
4. Token saved to `~/.rmapi` — future runs are automatic
## Commands
```bash
# List files/folders
rmapi ls
rmapi ls --json
# Navigate
rmapi cd "folder name"
# Find by tag / starred / regex
rmapi find --tag="share-with-gandalf" /
rmapi find --starred /
rmapi find / ".*sketch.*"
# Download (PDF)
rmapi get "filename"
# Download with annotations rendered (best for sketches)
rmapi geta "filename"
# Bulk download folder
rmapi mget -o ~/clawd/remarkable-sync/ "/Shared with Gandalf"
```
## Sharing Workflows
### Option A: Dedicated Folder
User creates "Shared with Gandalf" folder on reMarkable → moves items there → agent fetches with `rmapi mget`
### Option B: Tag-Based
User tags documents with `share-with-gandalf` → agent discovers with `rmapi find --tag`
### Option C: Starred Items
User stars items → agent fetches with `rmapi find --starred`
## Fetch Script
```bash
# Fetch from shared folder
~/clawd/scripts/remarkable-fetch.sh
# Fetch starred items
~/clawd/scripts/remarkable-fetch.sh --starred
# Fetch by tag
~/clawd/scripts/remarkable-fetch.sh --tag="share-with-gandalf"
```
## Notes
- Tablet must cloud-sync before files are available
- `geta` renders annotations into PDF (preferred for handwritten content)
- Use `convert` (ImageMagick) to go from PDF → PNG for image processing
- For text extraction, interpret the handwriting visually (vision model) rather than traditional OCR
Related in Image & Video
watch
IncludedWatch a video (URL or local path). Downloads with yt-dlp, extracts auto-scaled frames with ffmpeg, pulls the transcript from captions (or Whisper API fallback), and hands the result to Claude so it can answer questions about what's in the video.
physical-ai-defect-image-generation
IncludedUse when the user wants to orchestrate defect image generation, run associated setup, or handle outputs on OSMO. The Day 0 path handles cold-start with USD-to-ROI, image-edit augmentation, and AnomalyGen to create initial PCBA datasets. The Day 1 path performs inference and labeling on real images. This skill helps with first-time asset setup, creation of finetuning checkpoints, and configuring deployment. Trigger keywords: defect image generation, dig workflow, dig pipeline, defect image detection workflow, aoi pipeline, aoi anomalygen, usd2roi anomalygen, day 0 pcba, day 1 pcba, day 1 real-photo alignment, day 1 manual roi, metal surface anomaly, glass defect, anomalygen finetune, setup_pcb, setup_metal, setup_glass, setup_pretrained, dig setup, dig datasets, dig pretrained checkpoint, dig image-edit endpoint.
accelint-react-best-practices
IncludedReact performance optimization and best practices. ALWAYS use this skill when working with any React code - writing components, hooks, JSX; refactoring; optimizing re-renders, memoization, state management; reviewing for performance; fixing hydration mismatches; debugging infinite re-renders, stale closures, input focus loss, animations restarting; preventing remounting; implementing transitions, lazy initialization, effect dependencies. Even simple React tasks benefit from these patterns. Covers React 19+ (useEffectEvent, Activity, ref props). Triggers - useEffect, useState, useMemo, useCallback, memo, inline components, nested components, components inside components, re-render, performance, hydration, SSR, Next.js, useDeferredValue, combined hooks.
elevenlabs-agents
IncludedBuild conversational AI voice agents with ElevenLabs Platform using React, JavaScript, React Native, or Swift SDKs. Configure agents, tools (client/server/MCP), RAG knowledge bases, multi-voice, and Scribe real-time STT. Use when: building voice chat interfaces, implementing AI phone agents with Twilio, configuring agent workflows or tools, adding RAG knowledge bases, testing with CLI "agents as code", or troubleshooting deprecated @11labs packages, Android audio cutoff, CSP violations, dynamic variables, or WebRTC config. Keywords: ElevenLabs Agents, ElevenLabs voice agents, AI voice agents, conversational AI, @elevenlabs/react, @elevenlabs/client, @elevenlabs/react-native, @elevenlabs/elevenlabs-js, @elevenlabs/agents-cli, elevenlabs SDK, voice AI, TTS, text-to-speech, ASR, speech recognition, turn-taking model, WebRTC voice, WebSocket voice, ElevenLabs conversation, agent system prompt, agent tools, agent knowledge base, RAG voice agents, multi-voice agents, pronunciation dictionary, voice speed control, elevenlabs scribe, @11labs deprecated, Android audio cutoff, CSP violation elevenlabs, dynamic variables elevenlabs, case-sensitive tool names, webhook authentication
humanizer
IncludedHumanize AI-generated text by detecting and removing patterns typical of LLM output. Rewrites text to sound natural, specific, and human. Uses 28 pattern detectors, 560+ AI vocabulary terms across 3 tiers, and statistical analysis (burstiness, type-token ratio, readability) for comprehensive detection. Use when asked to humanize text, de-AI writing, make content sound more natural/human, review writing for AI patterns, score text for AI detection, or improve AI-generated drafts. Covers content, language, style, communication, and filler categories.
generating-mermaid-diagrams
IncludedSalesforce architecture diagrams using Mermaid with ASCII fallback. Use this skill when generating text-based diagrams for Salesforce architecture, OAuth flows, ERDs, integration sequences, or Agentforce structure. TRIGGER when: user says "diagram", "visualize", "ERD", or asks for sequence diagrams, flowcharts, class diagrams, or architecture visualizations in Mermaid. DO NOT TRIGGER when: user wants PNG/SVG image output (use generating-visual-diagrams), or asks about non-Salesforce systems.