# stormydayy/halo-overlay > Halo is a lightweight open-source AI overlay that listens to live conversations, sees your screen, and suggests what to say or do in the moment. It works with any OpenAI-compatible model and supports local Whisper for speech recognition. - Magnitude: 5.6 out of 10 — Early signal - Stars: 266 total · +109 stars measured 2026-10-27, 14:16–17:08 UTC, ≈ 139 by evening - Star trust: star growth looks organic - Category: AI agents · Language: Python · License: GPL-3.0 · Created: 2026-10-25 · Last push: 2026-10-25 - GitHub: https://github.com/stormydayy/halo-overlay · Page: https://gitnova.dev/en/r/stormydayy/halo-overlay ## Useful for - Run a live interview session with real-time answer suggestions from the overlay. - Use Rewind to recover the last few minutes of a meeting you zoned out of. - Set up a fully local pipeline with Ollama and whisper.cpp for private use. ## Why it’s here - Star-counter measurements on 2026-10-27 (UTC), 14:16–17:08: 157 → 266 stars (+109). This is the change over that interval. - Estimated end-of-day forecast: about +139 stars, using observed gains and the previous day. - The repository is 2 days old and already has 266 stars. With less than two weeks of history, there's no usual pace to compare the spike against yet. - Top new repositories this week: #74. - About 241 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: 36 - Issues and pull requests: 0 - Watchers: 4 - Average over the last week: 46 per day - Usual pace: too little history (under two weeks) - Stars in the last hour (measured): 48 ## Stars per day, last 3 days (oldest → newest, today is partial) 2026-10-25 … 2026-10-27: 0, 0, 109 ## Spotted in now - Top new repositories this week: #74 ## More in this category 1. **HKUDS/DeepTutor** — 8.8 · Breakout · AI agents · Python · +1,605 stars measured 2026-10-27, 00:34–17:07 UTC, ≈ 2,157 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** — 8.5 · Breakout · AI agents · Python · +1,060 stars measured 2026-10-27, 00:34–17:07 UTC, ≈ 1,475 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** — 8.3 · Breakout · AI agents · TypeScript · +835 stars measured 2026-10-27, 00:34–17:07 UTC, ≈ 1,184 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. **elayadesign/ai-design-skills** — 8.3 · Breakout · AI agents · +1,032 stars measured 2026-10-27, 00:34–17:07 UTC, ≈ 1,457 by evening A collection of markdown-based design skills for AI coding tools like Claude Code, Cursor, Codex and Windsurf, covering landing page design and turning static designs into animated showcases. Full card: https://gitnova.dev/en/r/elayadesign/ai-design-skills.md 5. **t3dotgg/tstack** — 8.0 · Breakout · AI agents · Python · +330 stars measured 2026-10-27, 00:34–17:07 UTC, ≈ 540 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 --- 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 17:24 UTC, updated every 30 minutes.