
Thought Based Reasoning
This is a structured prompting framework that makes Claude show its work on complex problems. You get six different techniques depending on what you're doing: zero-shot chain of thought for quick reasoning boosts, self-consistency when you need confidence scores, tree of thoughts for puzzles, least-to-most for breaking down dependencies, ReAct for grounding answers in real lookups, and PAL for generating Python to eliminate arithmetic errors. The decision matrix and templates are actually useful, not just theory. ClawFu claims 20-70% accuracy gains on the techniques, which tracks with the academic literature these are pulled from. Worth trying when you catch Claude hedging or making dumb math mistakes.
- skills.sh installs
- 308
- GitHub stars
- 150
- last updated
- Aug 21, 2026
Install
$ npx -y skills add guia-matthieu/clawfu-skills --skill thought-based-reasoning --agent claude-codeInstalls into .claude/skills of the current project.
Files
Thought-Based Reasoning
Overview
Core principle: Making reasoning explicit improves accuracy 20-70% on complex tasks.
Instead of jumping to answers, decompose problems into steps. This catches errors, enables backtracking, and produces verifiable reasoning.
When to Use
digraph decide {
"Problem type?" [shape=diamond];
"Direct answer worked?" [shape=diamond];
"Need confidence?" [shape=diamond];
"Use direct prompting" [shape=box];
"Use Zero-shot CoT" [shape=box];
"Use Self-Consistency" [shape=box];
"Use technique from table" [shape=box];
"Problem type?" -> "Direct answer worked?" [label="simple"];
"Problem type?" -> "Use technique from table" [label="math/logic/creative"];
"Direct answer worked?" -> "Use direct prompting" [label="yes"];
"Direct answer worked?" -> "Need confidence?" [label="no"];
"Need confidence?" -> "Use Self-Consistency" [label="yes, high stakes"];
"Need confidence?" -> "Use Zero-shot CoT" [label="no, just need better"];
}
Sponsors
Details
- Repository
- github.com/guia-matthieu/clawfu-skills
- First seen
- Jun 3, 2026
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