Split config: VRAM/model settings to config.md, agent behavior to AGENT.md
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# Framework Configuration
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This file contains global framework settings that apply across all projects.
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## VRAM Configuration
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Settings for task decomposition based on available VRAM.
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- **Auto-detect**: Yes # Detect GPU VRAM, RAM, and model context window automatically
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- **Target context**: 16k tokens # Override auto-detect if needed
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- **Headroom**: 25% # Leave headroom for code, context, and reasoning
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- **Max peak context per sub-task**: 12k tokens # Max context for any single sub-task
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### Auto-detection
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When `Auto-detect: Yes`, the framework probes your system to detect:
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- GPU VRAM (via `nvidia-smi` or `lspci`)
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- System RAM (via `free`)
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- Model context window (via API config or model name lookup)
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- Framework overhead (by reading all loaded prompt files)
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To disable auto-detection and use manual values:
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```
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## VRAM Configuration
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- **Auto-detect**: No
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- **Target context**: 8k
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- **Headroom**: 30%
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- **Max peak context per sub-task**: 5.6k
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```
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## Model Configuration
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Settings for the LLM model being used.
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- **Model**: auto # Use auto-detection from API config, or specify explicitly (e.g., gpt-4o, claude-3-5-sonnet)
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- **Override context window**: auto # Override auto-detection, or specify (e.g., 128k, 200k)
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### Auto-detection
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When `Model: auto`, the framework detects the model name from:
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1. `AGENT.md` in the project (if specified there)
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2. API config files (`.env`, `config.yaml`, `config.json`, etc.)
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3. Model name lookup by name (e.g., gpt-4o → 128k, claude-3-5-sonnet → 200k)
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To disable auto-detection and use manual values:
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```
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## Model Configuration
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- **Model**: gpt-4o
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- **Override context window**: 128k
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```
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## System Requirements
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Requirements for the environment the framework runs in.
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- **nvidia-smi**: Required if NVIDIA GPU (for VRAM detection)
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- **lspci**: Fallback if NVIDIA GPU not available (for AMD GPU VRAM detection)
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- **/proc/meminfo**: Required for RAM detection (Linux)
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- **sysctl**: Fallback for RAM detection (macOS)
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