Visual canvas for drawing full-stack architecture as typed nodes, exportable as JSON/YAML for AI coding tools
SpecRabbit is a visual canvas tool that lets developers draw full-stack architecture as typed nodes (UI forms, API endpoints, backend services, databases) connected by named flows. It captures global tech stack parameters and exports the specification as JSON or YAML for use by AI coding agents like Claude. The tool was built using Claude as a coding assistant and solves the problem of creating structured architecture specs that AI tools can consume.
Visit project ↗Entities
Related
Developer shares practical AI coding workflow: paper first, then Fable/Opus for planning, Sonnet for implementation
A developer on Reddit outlines a structured AI-assisted coding workflow for full projects, emphasizing upfront planning on paper before involving any model. The pipeline uses Fable for planning, Fable/Opus to break work into markdown files, and Sonnet for implementation under a safety hook, contrasting with the common 'vibe coding in agent mode' approach.
Enola: engineering intelligence layer for AI coding agents
Enola is an open-source engineering intelligence layer that helps AI coding agents understand existing codebases. It answers questions about change impact, dependency reachability, safe module deletion, refactoring priorities, and architecture drift. The tool uses LLMs to analyze code context and provide insights that reduce mistakes from both humans and AI agents.
CleanSlate IDE with built-in agent manager for multi-agent coding workflows
CleanSlate is an IDE that integrates an agent manager directly, allowing developers to create, manage, and switch between multiple coding agents without leaving the editor. It solves the friction of toggling between separate agent management tools and the IDE, enabling seamless context preservation and multi-agent orchestration for developers working with LLM-powered coding agents.
Live Kanban board for AI agent plans from plan.yaml
Plandeck renders a plan.yaml as a live Kanban board that auto-organizes tasks as an AI agent works. It computes task readiness from dependency edges, so the agent and user always see what is ready, blocked, or done, solving the problem of agents losing context or mis-prioritizing during long runs.
abap_wiki: Agent-driven engine turns SAP S/4HANA custom objects into citable Markdown/Obsidian knowledge base
A new open-source tool, abap_wiki, uses AI agents to extract SAP/ABAP custom objects from S/4HANA systems and convert them into citable Markdown/Obsidian pages. The engine aims to create a verifiable, AI-native knowledge base for both humans and AI agents, differentiating itself from simple RAG by providing structured, citable context. The project includes a measured benchmark for model selection.