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mm

Use this skill when the user wants to work with multimodal files (images, video, audio, PDFs, binary formats) — find, inspect, extract content, search, or count files using UNIX-style commands with multimodal powers.

Quellinformationen

Repository
javimosch/supercli
Letzte Quellaktivität
16. Juli 2026 um 20:46
Erkannte Sprache von SKILL.md
Englisch
Sterne
51
Forks
7

Installationsoptionen

Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.

Quelldateien prüfen

Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.

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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
mm
description
Use this skill when the user wants to work with multimodal files (images, video, audio, PDFs, binary formats) — find, inspect, extract content, search, or count files using UNIX-style commands with multimodal powers.
# mm Plugin Fast, multimodal context for agents. Familiar UNIX CLI tools like `find`, `grep`, `cat` — with multimodal powers. Rust core for speed, Python for dev-ex, UNIX philosophy for composability. `mm` enables agents to work with file types that LLMs can't natively read, including images, video, audio, PDFs, and other binary formats. Indexing is implicit — every command auto-builds a metadata index on first use. ## Commands ### Discovery - `mm find list --path <dir>` — Find/list files with multimodal metadata (tree, tabular, schema, JSON) - `mm find list --path <dir> --tree` — Hierarchical tree view with sizes - `mm find list --path <dir> --kind image` — Filter by kind (image, video, audio, document, code, text) - `mm wc count --path <dir> --by_kind` — Count files, bytes, lines, tokens by kind - `mm peek metadata --path <file>` — Raw file metadata (dimensions, EXIF, codec, duration, mime, hash) ### Content extraction - `mm cat extract --path <file>` — Extract content (PDF text, image captions, video descriptions, audio transcripts) - `mm cat extract --path <file> --mode accurate` — Full LLM pipeline (requires configured profile) - `mm cat extract --path <file> --lines 20` — First N lines (head) ### Search - `mm grep search --pattern <query> --path <dir>` — Text + semantic content search - `mm grep search --pattern <query> --path <dir> --semantic` — Semantic (vector) search - `mm sql query --query "SELECT * FROM files WHERE kind='image'"` — SQL on file metadata ### Config - `mm config show` — Show configuration and diagnostics - `mm profile list` — List LLM provider profiles - `mm self version` — Print mm version ### Passthrough - `mm _ _` — Passthrough to mm CLI with full argument access ## Usage Examples - "Find all images in ~/Downloads and show their sizes" - "Extract text from invoice.pdf" - "Search for 'invoice' across all PDFs in ~/docs" - "Count files by type in ~/data" - "Get a caption for photo.jpg using the accurate LLM pipeline" - "Run SQL queries on file metadata" ## Installation ```bash pip install mm-ctx ``` Alternative methods: ```bash # with uv uv pip install mm-ctx # run directly without installing uvx --from mm-ctx mm --help # macOS / Linux shell installer curl -LsSf https://vlm-run.github.io/mm/install/install.sh | sh ``` ## Examples ### Find files in a directory ```bash mm find ~/data --tree --depth 2 mm find ~/data --kind image --sort size --reverse --limit 20 mm find ~/data --format json ``` ### Extract content from files ```bash mm cat document.pdf # PDF text (fast pipeline) mm cat photo.jpg -m accurate # LLM caption + tags + objects mm cat video.mp4 -m accurate # Keyframe mosaic → LLM description mm cat audio.mp3 -m accurate # Whisper transcript ``` ### Search across files ```bash mm grep "invoice" ~/data/ mm grep "revenue forecast" ~/data/ -s # semantic search mm grep "TODO" ~/data/ --kind code ``` ### Inspect file metadata ```bash mm peek photo.jpg # image dimensions, EXIF, hash mm peek video.mp4 # video resolution, duration, codecs mm peek doc.pdf --full # include author, title, page count ``` ### Count files by kind ```bash mm wc ~/data --by-kind mm wc ~/data --by-kind --format json ``` ### SQL queries on indexed files ```bash mm sql "SELECT kind, COUNT(*) as n FROM files GROUP BY kind ORDER BY n DESC" --dir ~/data mm sql --list-tables ``` ## Key Features - UNIX-style commands (find, grep, cat, peek, wc, sql, bench) with multimodal semantics - Rust core for speed — metadata commands run in ~60ms on 700 files - Python API with `mm.Context` for building VLM-ready prompts incrementally - Auto-indexing on first use — no manual setup needed - Supports images, video, audio, PDFs, DOCX, PPTX, and text files - Two extraction modes: `fast` (default) and `accurate` (full LLM pipeline) - Semantic (vector) search across file contents - SQL queries on file metadata via SQLite - OpenAI and Gemini message format output - Optional audio transcription backends: MLX (Apple Silicon), ctranslate2 (GPU), OpenAI-compatible
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