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Local vision-language model for image analysis using SmolVLM-2B
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/tdimino/claude-code-minoan --skill smolvlmコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
Search, post, monitor, and archive on Twitter/X via five tools: the official hosted X MCP server (full-archive search, trends, bookmarks, Articles via xurl bridge), x-search CLI (cost-tracked API v2 research with calendar-day windows, volume counts, multi-query fan-out, feeds, watchlists, posting), xurl (official CLI for any endpoint incl. media/DMs), bird CLI (free session-based reads/writes, frozen at 0.8.0), and Smaug bookmark archival. Triggers on: search tweets, tweets from today, what did X tweet, latest tweets from, tweet volume, expand a Twitter query, check Twitter for, post a tweet, tweet this, post to X, reply on Twitter, full-archive search, what's trending, check mentions, my mentions, timeline, DMs, monitor account, research topic on Twitter, my bookmarks, archive bookmarks.
Manage Claude Code sessions — search by topic or ID, browse recent sessions with full metadata (tags, summaries, titles, cost), view title/nickname history timelines, resume in Ghostty tabs, spawn interactive or headless sessions, monitor live sessions, and bootstrap new setups. Triggers on resume session, find session, list sessions, recent sessions, spawn session, session history, what was I working on, open in ghostty, title history, session nicknames.
Summon Claude Fable 5 (Mythos-class, xenos daimon) for long-horizon tasks. Handles model override, cost awareness, and task routing. Availability probed at invocation.
SOC 職業分類に基づく
SKILL.md を表示中
| name | smolvlm |
| description | Local vision-language model for image analysis using SmolVLM-2B |
| version | 1.0.0 |
Analyze images locally using SmolVLM-2B, a state-of-the-art compact vision-language model optimized for Apple Silicon via mlx-vlm.
python ~/.claude/skills/smolvlm/scripts/view_image.py /path/to/image.png
python ~/.claude/skills/smolvlm/scripts/view_image.py /path/to/image.png "What text is visible?"
# Extract text (OCR)
python ~/.claude/skills/smolvlm/scripts/view_image.py screenshot.png "Extract all text"
# UI analysis
python ~/.claude/skills/smolvlm/scripts/view_image.py ui.png "Describe the UI elements"
# Detailed description
python ~/.claude/skills/smolvlm/scripts/view_image.py photo.jpg --detailed
"Describe this image" - Basic description"Describe this image in detail, including colors, composition, and any text" - Comprehensive"Extract all visible text from this image""What text appears in this screenshot?""Read the text in this document""Describe the user interface elements""What buttons and controls are visible?""Identify the application and its current state""How many [objects] are in this image?""What color is the [object]?""Is there a [object] in this image?""What programming language is shown?""Describe what this code does""Identify any errors in this code screenshot"| Spec | Value |
|---|---|
| Model | SmolVLM-2B-Instruct |
| Size | ~4GB |
| Peak Memory | 5.8GB |
| Speed | ~94 tok/s (M-series) |
| Supported Formats | PNG, JPG, JPEG, GIF, WebP |
uv pip install mlx-vlm --system"Model not found": First run downloads the model (~4GB). Wait for completion.
Out of memory: Close other applications. Model needs ~6GB free RAM.
Slow first inference: Model loading takes 10-15s on first use, subsequent calls are faster.