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From ai-video-producer
Intelligent, preference-driven model recommendation across fal.ai, Replicate, WaveSpeedAI, and MiniMax (Hailuo). Asks the user a short set of preference questions (workload, priority — quality vs speed vs cost, max budget per output, resolution/aspect/duration, NSFW tolerance, must-have features like lip-sync or audio), queries each available provider, and returns a ranked shortlist (3–5 options) with approximate per-output costs, quality/speed notes, and a recommendation. Differs from `model-researcher`: live-API backed, cost-first, and conversational about preferences.
npx claudepluginhub danielrosehill/claude-code-plugins --plugin ai-video-producerHow this skill is triggered — by the user, by Claude, or both
Slash command
/ai-video-producer:recommend-modelThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Conversational model picker. Use this when the user asks "what should I use for X" or "find me a cheap/good/fast model for X". For deep written research, use `model-researcher` instead.
Creates p5.js generative art with seeded randomness, noise fields, and interactive parameter exploration. Use for algorithmic art, flow fields, or particle systems.
Share bugs, ideas, or general feedback.
Conversational model picker. Use this when the user asks "what should I use for X" or "find me a cheap/good/fast model for X". For deep written research, use model-researcher instead.
Ask only the questions you don't already know from brief/creative-brief.md:
~/.config/ai-video-producer/.env.Keep this short — one batched message, not five round trips. Infer from the brief where possible.
Replicate (use the bundled MCP):
mcp__plugin_ai-video-producer_replicate__search_models with a query like the workload ("image-to-video", "lipsync", "upscaler").mcp__plugin_ai-video-producer_replicate__get_models for pricing/hardware metadata, and list_models_versions if a specific version is needed.fal.ai (hosted MCP exists for catalogue, but is thin — prefer web fetch):
WebFetch against https://fal.ai/models?categories=<category> and individual model pages (e.g. https://fal.ai/models/fal-ai/<slug>).runners/fal_run.mjs — confirm the model id matches the fal-ai/<slug> form the runner expects.WaveSpeedAI (no MCP — catalog via web):
WebFetch https://wavespeed.ai/models and individual model pages. Slugs follow wavespeed-ai/<family>/<variant> (e.g. wavespeed-ai/z-image/turbo).runners/wavespeed_run.py.MiniMax (Hailuo video, T2A speech, music — via the bundled minimax-mcp):
generate_video (Hailuo, including MiniMax-Hailuo-02 with 6s/10s @ 768P/1080P), text_to_image, text_to_audio, voice_clone, voice_design, music_generation.MiniMax-Hailuo-02 option explicitly when the user is choosing a text-to-video or image-to-video model.query_video_generation for async jobs.Always record the date checked. This space changes weekly.
Produce a compact table:
| Model | Provider | Approx cost/output | Quality | Speed | Notes |
Then a one-paragraph recommendation tied to the user's stated priority — and call out the tradeoff (e.g. "Kling 2.1 is ~3× the price of LTX but holds character identity over 10s; if you need <6s LTX is the better buy").
Cost approximates: state assumptions inline (e.g. "~$0.18 per 5s clip @ 720p, assuming the model's quoted 30s GPU time on A100"). Don't pretend to precision the providers don't give you.
If the user accepts a recommendation, offer to:
brief/tools-and-models.md (the canonical project-level model registry).research/recommendations-<workload>-<YYYY-MM-DD>.md for later reference.Don't write either file without confirmation.
WAVESPEED_API_KEY and MINIMAX_API_KEY.