Devon's Claude Code Skills Marketplace
Personal collection of Claude Code skills for PR automation and creative tasks.
Installation
Step 1: Add the Marketplace
Add this marketplace to Claude Code:
/plugin marketplace add devonjones/devon-claude-skills
Step 2: Install Plugins
Install the plugins you want to use:
# Install PR review loop
/plugin install pr-review-loop@devon-claude-skills
# Install image generation
/plugin install nano-banana@devon-claude-skills
# Install YouTube transcripts
/plugin install youtube-transcript@devon-claude-skills
# Install YouTube screenshotter
/plugin install youtube-screenshotter@devon-claude-skills
# Install YouTube synthesizer (recommended: install all three YouTube plugins together)
/plugin install youtube-synthesizer@devon-claude-skills
# Install article synthesizer
/plugin install article-synthesizer@devon-claude-skills
# Or install all
/plugin install pr-review-loop@devon-claude-skills nano-banana@devon-claude-skills youtube-transcript@devon-claude-skills youtube-screenshotter@devon-claude-skills youtube-synthesizer@devon-claude-skills article-synthesizer@devon-claude-skills
Step 3: Verify Installation
Check that the plugins are installed:
/plugin list
The skills will be automatically available for Claude to use.
Available Plugins
pr-review-loop
Automate PR review feedback loops with Gemini Code Assist, Cursor Bugbot, and Claude fallback.
Install:
/plugin install pr-review-loop@devon-claude-skills
Features:
- Autonomous review loop execution as Task agent
- Multi-bot support (Gemini Code Assist, Cursor Bugbot, Claude)
- Automatic comment resolution with reply templates
- Rate limit detection and fallback
- Skeptical review evaluation (not all suggestions should be implemented)
- Converges on one clean round — no round cap
Usage:
# Spawn autonomous review agent
Task tool:
subagent_type: general-purpose
model: sonnet
description: PR review loop for #<PR>
prompt: Execute the PR review feedback loop for PR #<PR>...
nano-banana
Generate, edit, and compose images using Google's Gemini 3 Pro Image model.
Install:
/plugin install nano-banana@devon-claude-skills
Features:
- Text-to-image generation with aspect ratio control
- Image editing with natural language instructions
- Multi-image composition (up to 14 reference images)
- Real-time data visualization with Google Search grounding
- Support for 1K, 2K, and 4K resolutions
Usage:
# Generate an image
scripts/generate_image.py "a serene landscape" output.png --aspect 16:9
# Edit an existing image
scripts/edit_image.py input.png "add a sunset" output.png
# Compose multiple images
scripts/compose_images.py "combine these" output.png img1.png img2.png img3.png
youtube-transcript
Extract transcripts (auto-generated or uploaded) from YouTube videos.
Install:
/plugin install youtube-transcript@devon-claude-skills
Features:
- URL parsing for
watch?v=, youtu.be/, youtube.com/shorts/, youtube.com/embed/, and bare 11-character video IDs
- Plain text or
[MM:SS] / [HH:MM:SS] timestamped output
- Language preference via
--lang
- Direct file output via
-o PATH
- Dependencies installed in an ephemeral per-invocation venv via
uv run --script (no persistent Python install pollution)
Usage:
# Plain transcript to stdout
scripts/get_transcript.py "https://www.youtube.com/watch?v=VIDEO_ID"
# With timestamps
scripts/get_transcript.py "VIDEO_ID" --timestamps
# Specific language, write to a file
scripts/get_transcript.py "VIDEO_ID" --lang en -o transcript.txt
youtube-screenshotter
Download a YouTube video at 720p and extract frames at specified timestamps with perceptual hashes. Mechanical only — pairs with youtube-synthesizer (which adds the smart bisection + visual-diff judgment) or any other downstream tool that needs frames + pHashes.
Install:
/plugin install youtube-screenshotter@devon-claude-skills
Features:
- Single
extract.py CLI batches yt-dlp download + ffmpeg frame extraction + pHash computation
- Manifest JSON output: video metadata block + per-frame entries
{timestamp, frame_path, phash}
- Cached on disk: video file by
<video_id>.mp4, frames by t<ms>.png — repeat invocations are cheap
- Sub-scripts also runnable independently:
video.py (download/metadata), frames.py (frame extraction), phash.py (compute / 3-band Hamming classifier)
- Dependencies via
uv run --script (yt-dlp, imagehash, Pillow)
Usage:
# Extract frames at given timestamps + emit manifest JSON
scripts/extract.py "https://www.youtube.com/watch?v=VIDEO_ID" -t 1 -t 30 -t 500 -o ./out
# Just metadata, no download
scripts/video.py "VIDEO_ID" --no-download
# Compute pHash of one image; compare two
scripts/phash.py compute frame.png
scripts/phash.py compare frame_a.png frame_b.png
youtube-synthesizer
Ingest a YouTube video as a faithful-capture literature note in an Obsidian vault. Combines transcript + canonical visual scenes + structured extraction (TL;DR, takeaways, references, code, tags). The smart layer on top of youtube-transcript and youtube-screenshotter — drives a bisection + visual-diff judgment loop using the agent's native vision capability (no separate API calls).
Install:
/plugin install youtube-synthesizer@devon-claude-skills
Recommended companions: youtube-transcript and youtube-screenshotter (this skill orchestrates them).
Features:
- Faithful capture, no editorializing — the entry preserves what the video communicated; weaving content into your mental model stays in your hands
- Per-note folder under
<vault>/sources/videos/<ingested-date>-<sanitized-title>/ so each entry self-contains its assets and is portable
- Frontmatter follows a stable base schema shared with future article/pdf/substack source-skills, plus YouTube-specific extras (
channel_id, playlist_id, chapter_markers, etc.) — designed for a future sqlite3 corpus indexer
- Hierarchical (chapter → scenes) when chapter markers exist; flat for short videos
- Skip-by-default if entry already exists;
--rerun to overwrite
- All inference runs on your existing Claude Code session — no separate
ANTHROPIC_API_KEY
Usage:
The skill is invoked via natural language or slash command, not a CLI script. Provide a video URL and a target vault path:
Use the youtube-synthesizer skill to ingest
https://www.youtube.com/watch?v=VIDEO_ID into ~/Obsidian/woodworking
Optional flags interpreted by the skill: --rerun to overwrite an existing entry, --why "<reason>" to seed the why_ingested frontmatter field.
article-synthesizer
Ingest a web article as a faithful-capture literature note in an Obsidian vault. The article sibling of youtube-synthesizer — same vault conventions and shared frontmatter base schema, no frame pipeline. Fetches via the WebFetch tool (curl fallback), refuses paywalled/login-walled/unfetchable pages rather than fabricating content.
Install:
/plugin install article-synthesizer@devon-claude-skills
Features:
- Faithful capture, no editorializing — TL;DR, key takeaways, reflowed article prose preserving the author's own section headings, code blocks verbatim
- Per-note folder under
<vault>/sources/articles/<sanitized-domain>/<ingested-date>-<sanitized-title>/, grouping a site's articles the way youtube-synthesizer groups a channel's videos
- Frontmatter follows the same base schema as youtube-synthesizer plus article extras (
site_name, fetched_via, word_count, canonical_url)
- References extracted from the article's outbound links with keep/drop filtering
- Images linked at their remote URLs, not downloaded (no image pipeline in v1)
- Skip-by-default if entry already exists;
--rerun to overwrite
- Headless-invocable by cryo's drain worker (
DRAIN-DONE: / DRAIN-FAILED: protocol)
Usage:
Use the article-synthesizer skill to ingest
https://example.com/some-article into ~/ObsidianVaults/Programming
Optional flags interpreted by the skill: --rerun to overwrite an existing entry, --why "<reason>" to seed the why_ingested frontmatter field.
Migration Notice
These skills were previously hosted in separate repositories:
Prerequisites
pr-review-loop
gh CLI authenticated with GitHubgit installedpre-commit (optional, auto-detected)
nano-banana
- Python 3.8+
GEMINI_API_KEY environment variable- Dependencies:
pip install google-genai Pillow pyyaml
youtube-transcript
uv — installs the Python deps in an ephemeral venv per invocation. Install with curl -LsSf https://astral.sh/uv/install.sh | sh or pip install uv.- Network access to
youtube.com.
youtube-screenshotter
uv — installs Python deps (yt-dlp, imagehash, Pillow) in an ephemeral venv per invocation.ffmpeg — required for frame extraction and yt-dlp's video+audio merge. sudo apt install ffmpeg (Linux), brew install ffmpeg (macOS).- Network access to
youtube.com and googlevideo.com for downloads.
youtube-synthesizer
youtube-transcript and youtube-screenshotter plugins installed (transitively requires uv and ffmpeg)- Network access to YouTube
- A target Obsidian vault path (writable). Per-note folder convention; the skill writes only under
<vault>/sources/videos/.
article-synthesizer
- Network access to the article's host;
curl for the fallback fetch path
- A target Obsidian vault path (writable). Per-note folder convention; the skill writes only under
<vault>/sources/articles/.
License
MIT - See LICENSE for details.
