Understand the project
Practical overview
When it fits
Use it as a reference when experimenting with prompts for questions that require tracking a sequence of events or evaluating alternative reasoning paths.
Who it is for
- People learning prompt engineering for large language models.
- Developers considering a reusable reasoning prompt in an LLM workflow.
Documented uses
- Try a multi-perspective prompt on a complex question.
- Explore a prompt-based approach to iterative reasoning and self-correction.
Before you choose
Requirements & limits
- The demonstrated method is expressed as a prompt rather than a packaged application or API.
- The repository reports an example where ChatGPT 3.5 answers correctly, but also notes that model responses are non-deterministic.
- The repository identifies an MIT license.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Source-based practical guide
Add a Chain-of-Thought instruction to a prompt
Encourage an LLM to explain its answer to a question.
Before you start
- An LLM that accepts a text prompt.
Steps
Write the question in the prompt.
Add the instruction: “Think carefully and logically, explaining your answer.”
Submit the prompt to the LLM.
Expected outcome
The LLM is prompted to explain its answer, which the guide says can improve performance on many questions.
Guide limitations
- Responses from LLMs can be non-deterministic.
- The source discusses this instruction as Chain-of-Thought prompting; it does not provide the complete Tree-of-Thought prompting procedure.
Evidence and transparency
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 6 November 2026
- Original website title
- dave1010/tree-of-thought-prompting · Official homepage title · retained in its source language