arcocodes/renoise-plugins-official/model-routing
Claude Code and agent skill by arcocodes/renoise-plugins-official
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Choose the best Renoise image, video, or audio model and write prompts for it. Always use before any Renoise generation estimate or task, and when the user asks for the best model, model comparison, model routing, which model to use, or “用哪个模型 / 模型选择”. Use alongside the active generation workflow; this Skill does not execute tasks.
Install
npx vskill@latest install arcocodes/renoise-plugins-official/model-routingSKILL.md
Renoise Model Routing
Select by task, not by habit. Then prompt for the selected model instead of sending every model the same generic brief.
Hard Boundary
Live model capabilities are authoritative for availability, defaults, input roles, combinations, limits, duration, ratio, resolution, and audio controls. This Skill contains only researched routing preferences and prompting styles.
- Preserve a model explicitly named by the user, or one you presented as selected in the plan or estimate. If it cannot do the job, explain why and the replacement you propose, and switch only after the user agrees.
- Filter candidates by the live capabilities required by the task.
- Route only to the newest live generation of a model family; older generations remain available only when the user explicitly names one.
- Choose the best specialist below.
- Use the live
isDefaultmodel only when no specialist clearly fits or candidates tie. - Inspect the selected model's live guidance before writing the final prompt.
- Let the selected model's profile override generic prompt-craft advice when prompt structure, density, or reference wording conflicts.
- Never pass a role or parameter merely because this guide mentions a public model capability; the Renoise deployment may expose a narrower contract.
Live availability alone is not a routing recommendation. Omit older generations, fully dominated models, and models without a clear task advantage; an explicitly named model still follows rule 1.
References and Edits
- Keep the authoritative identity or product references across iterative edits: send them in every related task alongside the latest composition or edit source, state each reference's job, and never treat a transformed intermediate as the replacement. When a reference limit forces a choice, keep the original anchor.
- For an edit or continuation, keep the source's aspect ratio when the model supports it; analyze the source when the ratio is unknown, and follow the model's live guidance for source-following ratios.
- Before generating with references, check every requirement the live capabilities state (format, duration, size, count) against what analysis or metadata shows. A source that breaks one would be rejected: convert or trim it with code first.
Routing Questions
Classify the request before selecting:
- Kind: image, video, or audio.
- Operation: create, edit, continue, interpolate, animate a reference, or upscale.
- Priority: final quality, strict instruction following, aesthetics, identity consistency, speed, or cost.
- Structure: exact text/layout, one cinematic shot, multi-shot narrative, dialogue performance, music, or a complete audio scene.
- References: none, one source image, several identity/style references, source video, endpoint frames, or voice/audio references.
Do not call a model “best” without naming the task it is best for.
Image Routing
Decision Order
| Task | Prefer | Why | |
|---|---|---|---|
| Exact text, UI, diagrams, ads, packaging, compositing, identity-sensitive image-to-image work, or peak final quality | gpt-image-2.6-sunburst | The default GPT Image model: route any GPT Image request that names no version here; use gpt-image-2.6-flare when explicitly requested. Image references guide transformations, but neither variant exposes mask inpainting. | |
| Animated GIF (loops, stickers, reaction images, simple motion) | gpt-image-2.6-sunburst with outputFormat: "gif" | The only live model that outputs a GIF. Pick a frame size (gifSize), a frame count within that size's range (frameCount) and a frame duration (frameDurationMs) from the live contract; a GIF takes no resolution or ratio and can take up to 16 reference images, but no mask. | |
| General high-quality photorealistic or commercial image | live image default | Start with the deployment's current default when no specialist better fits; do not infer local-edit or typography guarantees from the model family. | |
| Fast, inexpensive drafts and simple variants | grok-image | Lowest-cost live image tier for quick iteration; move the chosen direction to a specialist for the final. | |
| Extreme aspect ratios (1:4 to 8:1), Google-family work, several references, multilingual localization, or conversational iteration | nano-banana-2 | The Google-family model in the live lineup, balancing quality, latency, text, reference reasoning, and broad formats. | |
| Aesthetic exploration, stylized art direction, editorial mood, or concept art | mj-v8.2 | Current Midjourney generation and strong aesthetic prior. | |
| Seedream output resolution or image-reference count beyond what the live Pro contract accepts | seedream-5-0-lite | Choose Lite when its advertised limits fit and Pro's do not; otherwise use the live default for general Seedream work. | |
| xAI image request | grok-image for lower-cost iteration; grok-image-quality when higher quality justifies the added cost | Both support direct natural-language generation and editing through the live Renoise contract. |
Image Prompting Styles
GPT Image 2.6 — production brief
For complex production briefs, use labeled, ordered instructions:
- Route a generic GPT Image request to GPT Image 2.6 Sunburst; use Flare when explicitly requested. Neither live contract supports mask inpainting.
- For a GIF, describe the motion across the loop (what moves, from where to where, and how it returns to the first frame); keep the subject and background stable so the frames read as one shot.
- Put literal in-image text in quotes and specify hierarchy and placement.
- For image-to-image transformations, say change only X; preserve everything else.
- Identify every reference by its job: source, identity, product, layout, or style.
- Prefer one-change iterations over rewriting the whole brief; do not promise mask inpainting.
Nano Banana 2 — conversational creative direction
- Start with a clear operation verb and use positive, concrete natural language.
- For references, state each source's job, the relationship among them, and the new scenario.
- For edits, separate the requested change from what remains unchanged; repeat preservation requirements on later turns.
- Quote exact visible copy and specify its hierarchy, placement, visual character, and localization target.
- Relate multiple references explicitly and iterate conversationally.
Seedream 5 — design brief
Put the deliverable format first, then subject, layout, light, exact text, and invariants:
- Pro: specify dense layout, multilingual copy, materials, local edit regions, and everything the edit preserves.
- Lite: natural language works well; make causal/spatial relationships explicit for complex transformations.
- Assign each reference a clear role and avoid vague pronouns in multi-reference edits.
Midjourney — aesthetic visual phrase
Use a concise visual description, not a requirements document:
- Prefer concrete visual nouns and adjectives over keyword spam.
- Name the lighting and composition that matter instead of relying on “cinematic.”
- Use Midjourney for look development rather than text-heavy layouts or surgical edits.
Grok Imagine Image — concise scene direction
- Use standard for lower-cost iteration and Quality when the higher-quality tier is worth the added cost.
- For edits, attach the source image or images and describe the requested change directly.
- Keep the prompt concrete enough that the main subject and action remain dominant.
Video Routing
Decision Order
| Task | Prefer | Why | |
|---|---|---|---|
| General multimodal video, continuous 16–30 second sequences, rich mixed references, source-video edits, or forward/backward extension | seedance-2.5-byteplus | Newest Seedance generation and the long-form, reference-heavy specialist with precise edit/extension workflows. | |
| Budget multimodal video: brief shots up to 30 seconds and 1080p with a few image/video/audio references, text-to-video, or first(/last)-frame generation, when Seedance 2.5's long-form, edit, or extension strengths are not needed | wan3.0-video | About a third of Seedance 2.5's per-second price with broad reference support; it cannot edit, extend, or continue a source video, and frame and reference modes do not mix. | |
| Same as Wan 3.0 when turnaround matters more than cost | wan3.0-video-prime | Identical capabilities, faster on longer and higher-resolution jobs, and about 1.5× Wan 3.0's per-second price; prefer plain Wan 3.0 otherwise. | |
| Short 720p generation, text rendering, or source-video edit within its narrow live contract | gemini-omni-flash | Strong short-form instruction following, multi-shot generation, and conversational editing. | |
| H3-family 2K delivery, high-fidelity endpoint control, or focused multimodal references | hailuo-h3 | Full-quality tier with image/video/audio references; choose it when Max's live contract cannot meet the task. | |
| Fast H3-family text-to-video, first/last-frame, or reference-to-video with image/video/audio sources | hailuo-h3-max | Faster multimodal tier when its live quality and resolution fit; suitable for source-video variants without discarding the source. | |
| Fastest, lowest-cost H3-family text-to-video or first/last-frame generation without generic references | h3-max-turbo | Turbo supports text and endpoint frames, not reference image/video/audio inputs; use H3 Max or H3 for references. | |
| A single shot delivered at 2K or 4K from text or first(/last) frames, with native sound and no other references | flux-3-video | The only live model with 4K output (2K/4K upscaled from the same generation), 5–20 seconds, and cheaper per second than Seedance 2.5 at 1080p; it takes no reference images, video, or audio. | |
| xAI one-image animation with native sound | grok-video-1.5 | Newest Grok video generation; the current Renoise contract requires exactly one input image. | |
| Digital human: one person image talking or singing to a given voice track (talking head, presenter monologue, dubbed avatar, lip-synced song) | omnihuman-2.0 | Lip-syncs one portrait to one driving audio and runs as long as the audio (up to 300 seconds), so the exact voice and long monologues are controllable; it does not stage product handling or camera action the way generative video does. | |
| Upscale an existing video without changing its content | upscale-video-topaz-starlight-2.5 | Dedicated restoration/upscaling model; use a generation or editing model when objects, motion, timing, or style should change. |
Tier and version notes
This is the start of the file. Read the full SKILL.md on GitHub.
Security
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Source
- SKILL.md in the repositoryCheckingskills/model-routing/SKILL.md
Popularity
- Repository stars
- 12
- Repository forks
- 6
- 7-day trend score
- 13
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