Documentation Index
Fetch the complete documentation index at: https://docs.skaro.dev/llms.txt
Use this file to discover all available pages before exploring further.
Skaro supports four LLM providers out of the box. You can use one provider for everything, or mix them using role-based routing.
Provider Comparison
| Provider | API Key Required | Default Model | Console URL |
|---|
| Anthropic | Yes | claude-sonnet-4-6 | console.anthropic.com |
| OpenAI | Yes | gpt-5.2 | platform.openai.com |
| Groq | Yes | llama-3.3-70b-versatile | console.groq.com |
| Ollama | No | qwen3:32b | Local — ollama.com |
Available Models
Anthropic
| Model | Context Window | Max Output |
|---|
Claude Opus 4.6 (claude-opus-4-6) | 200K | 128K |
Claude Sonnet 4.6 (claude-sonnet-4-6) | 200K | 64K |
Claude Sonnet 4.5 (claude-sonnet-4-5-20250929) | 200K | 64K |
Claude Haiku 4.5 (claude-haiku-4-5-20251001) | 200K | 64K |
OpenAI
| Model | Context Window | Max Output |
|---|
GPT-5.2 (gpt-5.2) | 256K | 128K |
GPT-5.1 (gpt-5.1) | 256K | 128K |
GPT-5 (gpt-5) | 256K | 65K |
GPT-5 Mini (gpt-5-mini) | 256K | 65K |
GPT-5.2 Codex (gpt-5.2-codex) | 256K | 128K |
GPT-4.1 (gpt-4.1) | 1M | 32K |
GPT-4.1 Mini (gpt-4.1-mini) | 1M | 32K |
Groq
| Model | Context Window | Max Output |
|---|
Llama 3.3 70B (llama-3.3-70b-versatile) | 131K | 32K |
Llama 3.1 8B Instant (llama-3.1-8b-instant) | 131K | 131K |
GPT-OSS 120B (openai/gpt-oss-120b) | 131K | 65K |
Llama 4 Scout 17B (meta-llama/llama-4-scout-17b-16e-instruct) | 131K | 8K |
Kimi K2 (moonshotai/kimi-k2-instruct-0905) | 262K | 16K |
Qwen3 32B (qwen/qwen3-32b) | 131K | 40K |
Ollama (Local)
| Model | Context Window | Max Output |
|---|
Qwen3 32B (qwen3:32b) | 131K | 40K |
Qwen 3.5 35B (qwen3.5:35b) | 131K | 40K |
Llama 3.3 70B (llama3.3:70b) | 131K | 32K |
DeepSeek R1 70B (deepseek-r1:70b) | 131K | 65K |
Gemma 3 27B (gemma3:27b) | 131K | 8K |
Phi-4 14B (phi4:14b) | 16K | 16K |
CodeLlama 34B (codellama:34b) | 16K | 16K |
You can also enter any custom model ID during skaro init or via skaro config --model your-model-id. The lists above are suggestions, not hard limits.
Choosing a Provider
Best quality — Anthropic or OpenAI. Larger models produce better architecture reviews and more consistent code. Best for the architect role.
Fastest inference — Groq. Hardware-accelerated inference makes it excellent for code generation. Good for the coder role.
Full privacy — Ollama. Code never leaves your machine. No API costs. Trade-off: requires local hardware (16GB+ RAM for 30B+ models) and may produce lower quality output than cloud providers.
Cost-effective start — Groq offers a generous free tier. Good for trying Skaro without spending money.
Quick Setup
# Pick one:
skaro config --provider anthropic --api-key sk-ant-...
skaro config --provider openai --api-key sk-...
skaro config --provider groq --api-key gsk_...
skaro config --provider ollama --model qwen3:32b
