# A Plain-Text Reasoning Kernel for Alignment Research: The WFGY TXT OS Approach
In current AI alignment research, much of the challenge lies in reliably tracing, reproducing, and controlling the inner reasoning steps of large models. Existing tools for agent reasoning often lack transparency, modularity, or reproducibility—especially across LLM platforms.
Here I present an experimental open-source framework: a plain-text (TXT-based) reasoning engine that allows any LLM or agent to run interpretable, modular, and fully exportable semantic logic. Key alignment features include:
- **Semantic Tree Memory**: Enables long-term, window-independent reasoning traces, exportable for peer review. - **Knowledge Boundary Shield**: Real-time detection and flagging of hallucination or overreach in semantic reasoning. - **Formula-Driven Reasoning**: Every step is controlled by explicit, human-readable formulas, lowering the barrier for agent alignment prototyping.
All source code and reproducible test cases are freely available for the alignment research community:
A Plain-Text Reasoning Framework for Transparent AI Alignment Experiments
# A Plain-Text Reasoning Kernel for Alignment Research: The WFGY TXT OS Approach
In current AI alignment research, much of the challenge lies in reliably tracing, reproducing, and controlling the inner reasoning steps of large models. Existing tools for agent reasoning often lack transparency, modularity, or reproducibility—especially across LLM platforms.
Here I present an experimental open-source framework: a plain-text (TXT-based) reasoning engine that allows any LLM or agent to run interpretable, modular, and fully exportable semantic logic. Key alignment features include:
- **Semantic Tree Memory**: Enables long-term, window-independent reasoning traces, exportable for peer review.
- **Knowledge Boundary Shield**: Real-time detection and flagging of hallucination or overreach in semantic reasoning.
- **Formula-Driven Reasoning**: Every step is controlled by explicit, human-readable formulas, lowering the barrier for agent alignment prototyping.
All source code and reproducible test cases are freely available for the alignment research community:
https://github.com/onestardao/WFGY/tree/main/OS
Questions, critiques, and collaborative experiments are welcome!