tools/llm/llm-models/SKILL.md
Access Claude, Gemini, Kimi, GLM and 100+ LLMs via inference.sh CLI using OpenRouter. Models: Claude Opus 4.5, Claude Sonnet 4.5, Claude Haiku 4.5, Gemini 3 Pro, Kimi K2, GLM-4.6, Intellect 3. One API for all models with automatic fallback and cost optimization. Use for: AI assistants, code generation, reasoning, agents, chat, content generation. Triggers: claude api, openrouter, llm api, claude sonnet, claude opus, gemini api, kimi, language model, gpt alternative, anthropic api, ai model api, llm access, chat api, claude alternative, openai alternative
npx skillsauth add inference-sh/agent-skills llm-modelsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Access 100+ language models via inference.sh CLI.

Requires inference.sh CLI (
belt). Install instructions
belt login
# Call Claude Sonnet
belt app run openrouter/claude-sonnet-45 --input '{"prompt": "Explain quantum computing"}'
| Model | App ID | Best For |
|-------|--------|----------|
| Claude Opus 4.5 | openrouter/claude-opus-45 | Complex reasoning, coding |
| Claude Sonnet 4.5 | openrouter/claude-sonnet-45 | Balanced performance |
| Claude Haiku 4.5 | openrouter/claude-haiku-45 | Fast, economical |
| Gemini 3 Pro | openrouter/gemini-3-pro-preview | Google's latest |
| Kimi K2 Thinking | openrouter/kimi-k2-thinking | Multi-step reasoning |
| GLM-4.6 | openrouter/glm-46 | Open-source, coding |
| Intellect 3 | openrouter/intellect-3 | General purpose |
| Any Model | openrouter/any-model | Auto-selects best option |
belt app list --search "openrouter"
belt app list --search "claude"
belt app run openrouter/claude-opus-45 --input '{
"prompt": "Write a Python function to detect palindromes with comprehensive tests"
}'
belt app run openrouter/claude-sonnet-45 --input '{
"prompt": "Summarize the key concepts of machine learning"
}'
belt app run openrouter/claude-haiku-45 --input '{
"prompt": "Translate this to French: Hello, how are you?"
}'
belt app run openrouter/kimi-k2-thinking --input '{
"prompt": "Plan a step-by-step approach to build a web scraper"
}'
# Automatically picks the most cost-effective model
belt app run openrouter/any-model --input '{
"prompt": "What is the capital of France?"
}'
belt app sample openrouter/claude-sonnet-45 --save input.json
# Edit input.json:
# {
# "system": "You are a helpful coding assistant",
# "prompt": "How do I read a file in Python?"
# }
belt app run openrouter/claude-sonnet-45 --input input.json
# Full platform skill (all 250+ apps)
npx skills add inference-sh/skills@infsh-cli
# Web search (combine with LLMs for RAG)
npx skills add inference-sh/skills@web-search
# Image generation
npx skills add inference-sh/skills@ai-image-generation
# Video generation
npx skills add inference-sh/skills@ai-video-generation
Browse all apps: belt app list
development
Render videos from React/Remotion component code via inference.sh. Pass TSX code, get MP4. Supports all Remotion APIs: useCurrentFrame, useVideoConfig, spring, interpolate, AbsoluteFill, Sequence. Configurable resolution, FPS, duration, codec. Use for: programmatic video generation, animated graphics, motion design, data-driven videos, React animations to video. Triggers: remotion, render video from code, tsx to video, react video, programmatic video, remotion render, code to video, animated video, motion graphics code, react animation video
tools
Generate videos with Pruna P-Video and WAN models via inference.sh CLI. Models: P-Video, WAN-T2V, WAN-I2V. Capabilities: text-to-video, image-to-video, audio support, 720p/1080p, fast inference. Pruna optimizes models for speed without quality loss. Triggers: pruna video, p-video, pruna ai video, fast video generation, optimized video, wan t2v, wan i2v, economic video generation, cheap video generation, pruna text to video, pruna image to video
documentation
Still-to-video conversion guide: model selection, motion prompting, and camera movement. Covers Wan 2.5 i2v, Seedance, Fabric, Grok Video with when to use each. Use for: animating images, creating video from stills, adding motion, product animations. Triggers: image to video, i2v, animate image, still to video, add motion to image, image animation, photo to video, animate still, wan i2v, image2video, bring image to life, animate photo, motion from image
tools
Generate videos with Google Veo models via inference.sh CLI. Models: Veo 3.1, Veo 3.1 Fast, Veo 3, Veo 3 Fast, Veo 2. Capabilities: text-to-video, cinematic output, high quality video generation. Triggers: veo, google veo, veo 3, veo 2, veo 3.1, vertex ai video, google video generation, google video ai, veo model, veo video