| What it does | Fine-tuned small models for English-to-Bash command generation
| A coding agent CLI for local and hosted models
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| Stage | Not given
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| Founded | Not given
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| Based in | Not given
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| Pricing model | Open source
| Open source
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| Pricing | Not given
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| Key features | - 1.5B and 0.6B fine-tuned models
- 401,975 synthetic training examples
- 4-bit quantized models
- CLI with llama.cpp integration
- Command preview mode
- Covers file operations, text processing, Git, archives, networking
- Training data and checkpoints available
- Apache 2.0 and MIT licensed
- ALFA-updated benchmark evaluation
- Supervised fine-tuning with LoRA
| - Context discipline with prompt cache preservation
- Loop breaking detection and prevention
- Code verification with TypeScript typechecking
- Multiple work modes: plan, test-and-review, window, chat
- Kernel sandbox for shell commands on macOS
- Works with local and hosted models
- No telemetry
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| What makes it different | - 70.7% pass rate on ALFA-updated benchmark vs 63.7% for competing models
- CPU-friendly quantized models
- Specialized for bash command generation from natural language
- Agentically trained with synthetic data generation and evaluation
| - Designed specifically for small local models to reduce context waste and work efficiently
- Fails gracefully and communicates when stuck instead of spiraling
- Completely free and open source with no commercial edition or license key required
- Transparent and measured approach with A/B testing and published results
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| Free plan | Not given
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| Open source | Not given
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| Platforms | Not given
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| Public API | Not given
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| Community votes | 0 | 0 |
| DR (Domain Rating by Ahrefs) | 36 ● no change since last check | Not checked yet ● no change since last check |
| Trust Flow (Majestic) | 6 | 3 |
| Citation Flow (Majestic) | 32 | 19 |
| Referring domains (Majestic) | 219 | 14 |