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image

Generate or edit images on the user's own GPU through Guaardvark: single images, instruction edits, background cut-outs, inpaint and outpaint, consistent characters from the Cast Library, and batch runs of many prompts. Use when the user asks to create, draw, render, visualize, edit, or batch-generate images locally.

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SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Images with Guaardvark

Read setup first if the backend or the comfyui plugin state is unknown.

One image: MCP generate_image

  • prompt is scene, pose, lighting, setting. Plain prose. Do not paste JSON or tag soup; the default model (Z-Image Turbo) reads prompts as language, and SD-era tag lists hurt it.
  • model default auto picks the best downloaded model. Only override when the user names one: zimage-turbo, krea2-turbo, krea2-raw, flux-dev, sd-xl, sdxl-turbo, realistic-vision, epic-realism.
  • width / height: 512, 768 or 1024. style: realistic, artistic, anime, photographic, digital-art.
  • Consistent character: pass subject_ids=[<cast id>] as its own array. Never put the trigger word alone in the prompt and expect the LoRA to load. Find ids with GET /api/cast-library (see the cast skill).
  • On-image text: quote the exact words in double quotes inside the prompt.
  • The tool returns the image URL (/api/outputs/generated_images/<file>.png, relative to the backend), the model that ran, steps, seed and whether a Cast LoRA was applied. Show the URL and the prompt you used. Measured: 768x768 on Z-Image Turbo in ~20 s on a free 16 GB card.
  • Over MCP the call queues by default (wait_for_result defaults to false there) and returns Image queued as batch ImageBatch_... at once. Poll get_generation_status(batch_id=...) every few seconds until completed; it returns the file URL. Pass wait_for_result: true to block for the render instead (allowed up to 30 minutes). A call that exceeds the server's timeout answers with an error that says the render is still running; it is not lost.
  • A failed call carries the backend's reason (plugin off, out of memory, bad model). Read it and act on it; inspect_gpu and GET /api/plugins/status are the two checks that resolve most.

Photo edits over MCP run as jobs

edit_image, inpaint_image, outpaint_image and remove_background answer at once over MCP with ... queued as job tooljob_...: the work runs in the Guaardvark backend and keeps going if the client disconnects. Poll get_generation_status(batch_id="tooljob_...") every few seconds until done (it gives the file URL) or failed (it gives the error). Pass wait_for_result: true to wait up to 60 s (half the server's MCP timeout when that is shorter) for the result; a longer edit still comes back as the job id. A Qwen-Image-Edit takes about three minutes on a 16 GB card, and a job waits its turn while another render holds the GPU.

Edit an existing image: MCP edit_image

  • instruction is the change ("put a cowboy hat on him", "make the shirt red"). The image the user just attached is used automatically; otherwise pass image as a path or URL. Optional reference_image_2 / reference_image_3 (Qwen-Image-Edit only) for extra people or style; the call is refused when a reference cannot be read or the edit would run on another backend.
  • model auto uses Qwen-Image-Edit when installed, else FLUX.1 Kontext. With neither installed the call is refused and names the pack; relay that instead of retrying. Override with qwen-image-edit or kontext. Install those packs from Manage Image Models → Image editing (qwen-image-edit, flux-kontext-dev) — do not Install unless the user asked. Naming another downloaded image model runs a light img2img pass that keeps most of the picture.
  • Same canvas, same pose. For a brand-new picture use generate_image. For a new scene that keeps a face use generate_identity.

New scene from a face: MCP generate_identity (off by default)

  • Not exposed unless the server runs with GUAARDVARK_IDENTITY_TOOL=1: the likeness it keeps has not passed verification yet. If the tool is absent, say so and offer edit_image instead.
  • Attach a likeness the user has the right to use (their photo or a Cast subject they uploaded). consented must be true. Refuse if they have not confirmed that.
  • prompt is the new scene. Needs the PuLID identity pack (pulid-flux; Manage Image Models → Image editing installs it with its face files, EVA02-CLIP and flux-dev). Comfy must have been restarted after the PuLID-Flux custom node was added.
  • This is not a face swap onto an existing poster, and not an instruction edit of the same photo.

Background remove: MCP remove_background

  • Cuts the subject out of the attached photo (transparent PNG). ONNX matting, no diffusion; needs a background-removal model from Manage Image Models → Image editing.
  • For a new background, remove first then edit_image / generate_identity, or describe the new scene in edit_image if Qwen-Image-Edit is installed.

Inpaint / outpaint

  • inpaint_image: change or remove something ("remove the coffee cup"). Runs on Qwen-Image-Edit or FLUX.1 Kontext; refused when neither is installed.
  • outpaint_image: extend the canvas (left/right/top/bottom pixels) and fill. Prefers Qwen.

Many images: REST batch

B=${GUAARDVARK_URL:-http://localhost:5000}
curl -s -X POST $B/api/batch-image/generate/prompts -H 'Content-Type: application/json' -d '{
  "prompts": ["prompt one", "prompt two"],
  "model": "auto",
  "subject_ids": []
}'
  • prompts may be strings or {"prompt": "..."} objects. There is a per-batch maximum; if the server answers 400 "Too many prompts", split the list.
  • Optional adapters (user LoRAs from the models skill) and subject_ids (Cast Library).
  • The response is data.batch_id (ImageBatch_<date>_<n>). Poll GET $B/api/batch-image/status/<batch_id>?include_results=true: status goes running → completed, with completed_images / total_images, output_dir, and one results[] entry per prompt (success, image_path, thumbnail_path, generation_time, metadata.model_used). A contact sheet: GET $B/api/batch-image/preview/<batch_id>; one file: GET $B/api/batch-image/image/<batch_id>/<image_name> (the basename of image_path). Cancel with POST $B/api/batch-image/cancel/<batch_id>. Measured: one 1024x1024 prompt completed in ~30 s.
  • Helpers: POST /api/batch-image/enhance-prompt, /analyze-prompt, /expand-concept (JSON body with the prompt) when the user wants prompt help before spending GPU time.

Rules

  • Say which model actually ran (the response names it). Do not promise a model that is not installed.
  • Generation time depends on the GPU; a first image after Ollama held the card can take longer because the orchestrator swaps models. That is normal.
  • Never upload the user's images anywhere. Everything here is local.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

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概要と使いどころ

cast

無料

Build consistent characters, environments and props in Guaardvark's Cast Library and train LoRAs for them locally (reference photos → vision bible → sample plan → approved samples → training). Use when the user wants the same face or object across images, videos, a music video, or a Film Crew production, or asks to "train a LoRA".

日本語の概要は準備中です。原文の説明を表示しています。

guaardvark/guaardvark2582026年10月11日 更新

code

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Code intelligence over repositories Guaardvark has indexed: semantic code search, exact-text search, file listing, PageRank repository map, import dependency graph, reading one class or function, analysis and generated rewrites, plus the System Mapper and self-improvement status. Use when the user asks where something is implemented, how modules depend on each other, or wants an architecture map of an indexed repo.

日本語の概要は準備中です。原文の説明を表示しています。

guaardvark/guaardvark2582026年10月11日 更新

film-crew

無料

Run Guaardvark's five-role Film Crew locally: screenwriter, casting (Cast Library LoRAs), cinematographer storyboards, keyframe renders, editor. Turns a logline or screenplay into a finished short video with human gates at casting and storyboard. Use when the user says "film this", "make a short film", "storyboard this script", or "start the film crew".

日本語の概要は準備中です。原文の説明を表示しています。

guaardvark/guaardvark2582026年10月11日 更新

knowledge

無料

Answer from the user's own indexed documents with Guaardvark's local RAG, browse and read indexed files section by section, remember facts across sessions, and process or fetch new material. Use when the user asks what their documents say, wants a source-cited answer from their files, says "remember this", or asks to index a PDF, DOCX, spreadsheet, image or URL.

日本語の概要は準備中です。原文の説明を表示しています。

guaardvark/guaardvark2582026年10月11日 更新

models

無料

Add any Hugging Face image or video model, checkpoint or LoRA to Guaardvark from a URL, list what is installed, and download registry models on request. Use when the user pastes a huggingface.co link or a .safetensors URL, asks "can it run <model>", or wants a new LoRA or checkpoint available in the Studio.

日本語の概要は準備中です。原文の説明を表示しています。

guaardvark/guaardvark2582026年10月11日 更新

music

無料

Generate full songs with vocals or instrumentals (ACE-Step) and sound effects or ambience (Stable Audio Open) on the user's GPU through Guaardvark's Audio Foundry. Use when the user asks for a song, a beat, a jingle, background music, or a sound effect, made locally with no subscription.

日本語の概要は準備中です。原文の説明を表示しています。

guaardvark/guaardvark2582026年10月11日 更新

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