antigravity-workspace-template and shadxn

The two projects are competitors: one offers a starter kit for AI IDEs and agentic coding environments, while the other is an experiment in agentic code generation and component registry, suggesting overlapping goals in facilitating AI-driven development workflows.

shadxn
49
Emerging
Maintenance 25/25
Adoption 10/25
Maturity 13/25
Community 25/25
Maintenance 10/25
Adoption 12/25
Maturity 17/25
Community 10/25
Stars: 1,026
Forks: 207
Downloads:
Commits (30d): 59
Language: Python
License: MIT
Stars: 85
Forks: 7
Downloads: 15
Commits (30d): 0
Language: TypeScript
License:
No Package No Dependents
No License

About antigravity-workspace-template

study8677/antigravity-workspace-template

🪐 The ultimate starter kit for AI IDEs, Claude code,codex, and other agentic coding environments.

Deploys a dynamic multi-agent cluster where each code module gets its own Agent that autonomously generates knowledge docs during `ag-refresh`, with a Router that intelligently routes IDE queries via MCP to the responsible ModuleAgent—grounding context in actual source code rather than static docs. Supports Cursor, Claude Code, Windsurf, VS Code, and other agentic IDEs through portable `.antigravity/` folder architecture, using OpenAI Agent SDK and LiteLLM for multi-LLM compatibility. CLI injects templates zero-dependency, while the optional engine adds multi-agent Q&A, git history analysis, and optional semantic search via GitNexus integration.

About shadxn

anis-marrouchi/shadxn

Experimenting with AI our way into the unknown — monorepo: agentx (agentic code generation engine) + shadxn (component registry & transforms)

**agentx** orchestrates multi-step code generation via Claude using project context (tech stack, schemas, docs) with features like auto-healing, MCP server mode, and agent-to-agent communication. **shadxn** provides AST-based component registry management and code transforms (imports, CSS, JSX, RSC) across shadcn, aceternity, and custom component sources. Together they enable natural language-driven development workflows within a shared utility layer.

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