Guided first-time setup for Minutes — download whisper model, create directories, configure audio input. Use when the user says "set up minutes", "install minutes", "first time setup", "configure minutes", "get started with minutes", "how do I start using minutes", or when verify shows missing components.
npx skills add https://github.com/silverstein/minutes --skill minutes-setup
Walk the user through first-time Minutes setup, step by step.
Run the verify skill's script to see what's already done:
bash "${CLAUDE_PLUGIN_ROOT}/skills/minutes-verify/scripts/verify-setup.sh"
Skip any steps that already pass.
cd ~/Sites/minutes
export CXXFLAGS="-I$(xcrun --show-sdk-path)/usr/include/c++/v1"
cargo build --release
The binary lands at target/release/minutes. The user should add it to their PATH or create a symlink.
Ask the user which quality level they want using AskUserQuestion:
| Model | Size | Speed | Quality | Best for |
|-------|------|-------|---------|----------|
| tiny | 75 MB | ~10x real-time | Low | Quick tests, short memos |
| small | 466 MB | ~4x real-time | Good | Daily meetings (recommended) |
| medium | 1.5 GB | ~2x real-time | Great | Important meetings, accents |
| large-v3 | 3.1 GB | ~1x real-time | Best | Legal, medical, foreign language |
Then run:
minutes setup --model <chosen-model>
mkdir -p ~/meetings/memos
For in-person conversations, the built-in mic works fine. For Zoom/Meet/Teams:
brew install blackhole-2chSee minutes-record/references/audio-devices.md for the full guide.
Run verify again to confirm everything passes:
bash "${CLAUDE_PLUGIN_ROOT}/skills/minutes-verify/scripts/verify-setup.sh"
minutes record --title "Test recording"
# Speak for 10-15 seconds
minutes stop
Check the output file exists in ~/meetings/ and has a transcript.
small model is 466 MB. On slow connections, tiny is a good starting point (75 MB).Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
Improves the quality of images, especially screenshots, by enhancing resolution, sharpness, and clarity. Perfect for preparing images for presentations, documentation, or social media posts.
Downloads videos from YouTube and other platforms for offline viewing, editing, or archival. Handles various formats and quality options.
Lightweight WSI tile extraction and preprocessing. Use for basic slide processing tissue detection, tile extraction, stain normalization for H&E images. Best for simple pipelines, dataset preparation, quick tile-based analysis. For advanced spatial proteomics, multiplexed imaging, or deep learning pipelines use pathml.
Microscopy data management platform. Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing, for high-content screening and microscopy workflows.
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.
This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.
Take silverstein/minutes-minutes-setup 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.
The instructions reference brew.
Without those the skill loads but fails at the first command.