# daveebbelaar/bama

> Agent skills for building native macOS apps in Swift and SwiftUI: clone an existing app from screenshots, plan user stories, then build, design, optimize, and test it without opening Xcode.

- Magnitude: 5.7 out of 10 — Early signal
- Stars: 151 total · +16 stars measured 2026-10-27, 07:42–09:11 UTC, ≈ 70 by evening
- Star trust: star growth looks organic
- Category: AI agents · Language: Swift · License: MIT · Created: 2026-10-24 · Last push: 2026-10-27
- GitHub: https://github.com/daveebbelaar/bama · Page: https://gitnova.dev/en/r/daveebbelaar/bama

## Useful for

- Clone a to-do app as a native Mac app by screenshotting every screen and building milestone 1
- Build a window snapper from a spec in specs/ with BAMA
- Add a CLI and MCP server so Claude Code or Codex can drive your app

## Why it’s here

- Star-counter measurements on 2026-10-27 (UTC), 07:42–09:11: 135 → 151 stars (+16). This is the change over that interval.
- Estimated end-of-day forecast: about +70 stars, using observed gains and the previous day.
- The repository is 3 days old and already has 151 stars. With less than two weeks of history, there's no usual pace to compare the spike against yet.
- Top new repositories this week: #140.
- About 95 forks a day — people are taking the code.

## Star trust

Star growth looks organic.

Star-trust labels are heuristics based on the repository’s behavior, not a check of every stargazer.

## Numbers

- Forks: 29
- Issues and pull requests: 0
- Watchers: 1
- Average over the last week: 48 per day
- Usual pace: too little history (under two weeks)
- Stars in the last hour (measured): 13

## Stars per day, last 4 days (oldest → newest, today is partial)

2026-10-24 … 2026-10-27: 0, 0, 121, 16

## Spotted in now

- Top new repositories this week: #140

## More in this category

1. **HKUDS/DeepTutor** — 8.7 · Breakout · AI agents · Python · +724 stars measured 2026-10-27, 00:34–09:11 UTC, ≈ 1,698 by evening
   A lifelong personalized AI tutor with long-term memory: builds learning paths, reads documents and books, and runs practice and assessments via a multi-agent system and RAG.
   Full card: https://gitnova.dev/en/r/HKUDS/DeepTutor.md
2. **TauricResearch/TradingAgents** — 8.7 · Breakout · AI agents · Python · +677 stars measured 2026-10-27, 00:34–09:11 UTC, ≈ 1,685 by evening
   A framework that simulates a trading firm with LLM agents (analysts, researchers, trader, risk manager) debating markets and producing trading decisions. Built for research, not real trading.
   Full card: https://gitnova.dev/en/r/TauricResearch/TradingAgents.md
3. **makecindy/cindy** — 8.6 · Breakout · AI agents · TypeScript · +540 stars measured 2026-10-27, 00:34–09:11 UTC, ≈ 1,442 by evening
   Cindy is an open-source AI agent that combines multiple harnesses (Claude Code, Codex), models and tools into one agent working locally with your real files and apps. This repo is the client: Electron desktop and Expo/React Native mobile…
   Full card: https://gitnova.dev/en/r/makecindy/cindy.md
4. **t3dotgg/tstack** — 8.3 · Breakout · AI agents · Python · +177 stars measured 2026-10-27, 00:34–09:11 UTC, ≈ 861 by evening
   A collection of reusable agent skills for Claude Code and Codex that automate pull request workflows, from filing and reviewing to merging, plus peer review by multiple models.
   Full card: https://gitnova.dev/en/r/t3dotgg/tstack.md
5. **alchaincyf/huashu-design** — 8.1 · Breakout · AI agents · HTML · +751 stars measured 2026-10-27, 00:34–09:11 UTC, ≈ 1,546 by evening
   An HTML design skill for AI agents (Claude Code, Codex, Cursor) that turns a single prompt into deliverable designs: App/Web prototypes, editable PPTX, animations and infographics. Includes an 84-style library and a six-direction…
   Full card: https://gitnova.dev/en/r/alchaincyf/huashu-design.md

---

Magnitude (0–10) measures how fast and how unusually interest in a repository is growing right now. It is not a quality score.
Days are UTC. “So far today” is a fact; “expected by the end of the day” is a forecast.
Summaries and use cases are written by an LLM (DeepSeek V4.1 Flash) from the README and may be inaccurate: verify specific claims (benchmarks, speed, hardware) in the repository itself.
Data as of 2026-10-27 09:31 UTC, updated every 30 minutes.