zd8899/TDAD
Visual Test-Driven AI Development for AI Agents
Enforces a structured Plan → Spec → Test → Fix cycle using a visual canvas workflow that captures runtime feedback (execution traces, network requests, DOM snapshots) to guide AI code generation. Works as a VS Code extension that generates Gherkin specs and test scaffolding before implementation, then routes exact failure data back to the AI for surgical fixes. Operates entirely locally without API calls—compatible with Claude, ChatGPT, Cursor, or any AI agent you control.
Stars
55
Forks
8
Language
TypeScript
License
MIT
Category
Last pushed
Feb 17, 2026
Commits (30d)
0
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