Tree Of Thoughts

When you need to solve something complex and aren't sure which approach is best, this runs three agents in parallel to propose different solutions, then uses meta-judges to create custom evaluation criteria before voting on which proposals to pursue. The strong bit is the adaptive strategy: if there's a clear winner it polishes that solution, if everything scores poorly it redesigns from scratch, and if opinions split it synthesizes the best parts. It's structured around eight phases with proper pruning and expansion, saving all the research artifacts to `.specs/research` so you can see how it arrived at the answer. Probably overkill for straightforward tasks, but useful when the problem space is genuinely unclear and you want systematic exploration rather than going with your first instinct.

skills.sh installs: 1.2K
GitHub stars: 1.8K
last updated: Aug 21, 2026

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Install

$ npx -y skills add neolabhq/context-engineering-kit --skill tree-of-thoughts --agent claude-code

Installs into .claude/skills of the current project.

Files

tree-of-thoughts

Execute complex reasoning tasks through systematic exploration of solution space, pruning unpromising branches, expanding viable approaches, and synthesizing the best solution. This command implements the Tree of Thoughts (ToT) pattern for tasks requiring exploration of multiple solution paths before committing to full implementation. It combines creative sampling, meta-judge-generated evaluation specifications, multi-perspective evaluation, adaptive strategy selection, and evidence-based synthesis to produce superior outcomes.

Key benefits:

Systematic exploration - Multiple agents explore different regions of the solution space
Structured evaluation - Meta-judges produce tailored rubrics and criteria before judging
Independent verification - Judges apply meta-judge specifications mechanically, reducing bias
Adaptive strategy - Clear winners get polished, split decisions get synthesized, failures get redesigned