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# AGENTS.md
**Last Updated:** April 9, 2026
## Research Project: Coding Agent Harness Analysis
### Objective
Collect data and feedback on four coding agent harnesses to determine what works best for different model sizes, particularly smaller/local models.
### Harnesses Under Analysis
1. **opencode** - Go-based coding agent
2. **pi** (pi-mono) - Mario Zechner's minimal terminal coding agent
3. **hermes** - Nous Research's agent that grows with you
4. **forgecode** - AI pair programmer with sub-agents
### Data Collection Strategy
#### Performance Benchmarks
- Run terminal-bench and similar benchmarks across all harnesses
- Track relative performance metrics
- Document success rates, speed, and quality of outputs
#### Community Feedback Collection
Feedback organized by harness and model tier:
- `opencode/feedback/localllm/` - Community feedback for local models
- `opencode/feedback/frontier/` - Community feedback for frontier models
- `pi/feedback/localllm/` - Community feedback for local models
- `pi/feedback/frontier/` - Community feedback for frontier models
- `hermes/feedback/localllm/` - Community feedback for local models
- `hermes/feedback/frontier/` - Community feedback for frontier models
- `forgecode/feedback/localllm/` - Community feedback for local models
- `forgecode/feedback/frontier/` - Community feedback for frontier models
### Folder Structure
```
opencode/
repo/ - opencode-ai/opencode source
feedback/
localllm/ - Local model feedback
frontier/ - Frontier model feedback
pi/
repo/ - badlogic/pi-mono source
feedback/
localllm/ - Local model feedback
frontier/ - Frontier model feedback
hermes/
repo/ - NousResearch/hermes-agent source
feedback/
localllm/ - Local model feedback
frontier/ - Frontier model feedback
forgecode/
repo/ - antinomyhq/forgecode source
feedback/
localllm/ - Local model feedback
frontier/ - Frontier model feedback
```
### Research Focus Areas
- Tool handling and capabilities
- Skills system effectiveness
- Prompt engineering strategies
- Context management
- Error recovery and resilience
### Future Work
Eventually extract best practices and implement improvements specifically optimized for smaller/local models.
### Reference Materials
Files from `../entropy/Research/md/` contain prompt research and strategies:
- `Research.md` - General research methodology
- `Research-prompt.md` - Prompt engineering research and strategies
- `Research-orchestration.md` - Orchestration patterns and strategies
These files contain prompt research and strategies to reference during analysis.