Test specific theories about code behavior using Gemini AI. Analyze code scope, define hypotheses, and apply test approaches to validate assumptions in distributed systems and long-trace debugging.
Conduct competitive hypothesis tournaments to identify root causes by testing multiple theories in parallel. Uses evidence-based scoring and elimination rounds for efficient issue resolution.
Enhance complex reasoning with meta-cognitive assessment, hypothesis testing, and graph-based memory. Track confidence, validate evidence, and manage session context for systematic problem-solving and decision-making.
Apply structured scientific reasoning to solve problems by guiding users through hypothesis testing, variable identification, and evidence evaluation. Ideal for systematic inquiry and decision-making.
Create, manipulate, and interpret diagrams, graphs, and visual representations to facilitate insight generation, hypothesis testing, and problem-solving. Supports various visual elements and operations for structured reasoning and decision-making.
Enables AI-powered academic research workflow from keyword search to hypothesis generation. Integrates multiple AI models to automatically search ArXiv papers, extract key information, and generate innovative research hypotheses for researchers.
Provides a tool for dynamic and reflective problem-solving by breaking complex problems into manageable steps with support for revision, branching, and hypothesis generation.
An MCP server that enhances sequential thinking with meta-cognitive capabilities including confidence tracking, hypothesis testing, and organized memory storage through graph-based libraries and structured JSON documents.