Transforms AI coding tools into structured research engines for validating critical development decisions with evidence.
Sponsored
Tackle crucial development decisions with confidence by evolving your AI coding agent into a rigorous research engine. Wheat provides a structured framework for conducting research sprints, where every finding is captured as a typed, evidence-graded claim. Its powerful 7-pass compiler meticulously identifies contradictions, flags weak evidence, and ensures comprehensive coverage, blocking output until all issues are resolved. This guarantees that your final decision document is robustly backed by validated evidence, not subjective assumptions, preventing costly errors and ensuring informed strategic choices.
主要功能
01Structured research sprints for evidence-graded claims
027-pass compiler for conflict detection, evidence coverage, and type diversity
03Integration with AI coding tools like Claude Code, Cursor, and GitHub Copilot, or standalone CLI use
04Support for various claim types (factual, risk, recommendation) and evidence tiers (stated, tested, production)
05Optional guard rails including Git pre-commit hooks and Claude Code generation prevention
0619 GitHub stars
使用案例
01Validating large-scale migration or architectural decisions before implementation
02Ensuring consistency and evidence-backing for AI-generated advice over extended sessions
03Producing comprehensive decision documents with rigorously validated evidence for critical project choices
