graph-of-thoughts
Graph-based reasoning with thought combination and feedback loops. Explores multiple solution paths simultaneously, combines insights, and synthesizes optimal solutions. Use for: synthesis problems, optimization, creative combination, complex multi-dimensional problems.
Best for synthesis tasksWorks with GitHubLow risk
⌘source
- author
@LeoYeAI- language
- Python
★2kstars
306forks
May 6, 2026
✦overview.md
Key Features
- ·Multi-path thought exploration
- ·Cross-branch insight merging
- ·Feedback loops for iterative refinement
- ·Cost-effective via thought reuse
- ·Aggregation of multiple solutions
Use Cases
- →Synthesizing optimal solutions from multiple reasoning paths
- →Solving complex multi-dimensional problems with non-linear dependencies
- →Combining insights from different branches of thought
- →Iterative refinement of solutions via feedback loops
Best for
- ✓synthesis tasks
- ✓optimization problems
- ✓creative combination
Not ideal for
- !simple linear reasoning
- !single-solution tasks
FAQs
name
graph-of-thoughts
description
Graph-based reasoning with thought combination and feedback loops. Explores multiple solution paths simultaneously, combines insights, and synthesizes optimal solutions. Use for: synthesis problems, optimization, creative combination, complex multi-dimensional problems.
version:2.0.0
metadata:{"openclaw":{"emoji":"🕸️","os":["darwin","linux","win32"]}}
Graph of Thoughts (GoT) Reasoning
Advanced multi-path reasoning beyond tree structure. Explores, combines, and synthesizes solutions.
Research Foundation
Based on: Besta et al. (2024) - "Graph of Thoughts: Solving Elaborate Problems with Large Language Models" (AAAI)
Key Insight: Tree structure limits thought combination. Graphs allow:
- Merging insights from different branches
- Feedback loops for iterative refinement
- Non-linear dependencies between thoughts
- Aggregation and distillation of multiple solutions
Performance: +62% quality improvement on synthesis tasks, +31% cost reduction via thought reuse.
GoT vs ToT vs CoT
Chain of Thought (CoT)
Problem → Step 1 → Step 2 → Step 3 → Solution
(Single linear path, fast but limited)
Tree of Thoughts (ToT)
Problem
/ | \
A B C (independent branches)
/ \ | / \
A1 A2 B1 C1 C2 (no cross-branch combination)
|
Best A1
Graph of Thoughts (GoT)
Problem
/ | \
A ─── B ─── C (branches can connect)
/ \ │ / \
$install
1-click copynpx skills add LeoYeAI/openclaw-master-skills --skill graph-of-thoughtsSafety assessment
★
Clarity score
How clear and easy to understand the SKILL.md instructions are, rated from 1 to 5.
2/ 5
fairThe main idea is there, but the wording is messy and easy to misinterpret.
◎
Actionability score
How directly an agent can act on the SKILL.md instructions, rated from 1 to 5.
2/ 5
lowSome hints are present, but an agent still has to guess many steps.