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-producerThis skill uses the workspace's default tool permissions.
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.
Guides Next.js Cache Components and Partial Prerendering (PPR) with cacheComponents enabled. Implements 'use cache', cacheLife(), cacheTag(), revalidateTag(), static/dynamic optimization, and cache debugging.
Guides building MCP servers enabling LLMs to interact with external services via tools. Covers best practices, TypeScript/Node (MCP SDK), Python (FastMCP).
Generates original PNG/PDF visual art via design philosophy manifestos for posters, graphics, and static designs on user request.
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.