# zengshuangzi/mcd-money-saver > A skill that saves money on McDonald's orders: it gathers coupons, points and combos via McDonald's MCP and picks the cheapest order option. It accounts for budget and calories. - Magnitude: 4.7 out of 10 — Early signal - Stars: 145 total · +22 stars measured 2026-10-24, 13:51–18:41 UTC, ≈ 31 by evening - Star trust: star growth looks organic - Category: AI agents · Language: Python · Created: 2026-10-22 · Last push: 2026-10-23 - GitHub: https://github.com/zengshuangzi/mcd-money-saver · Page: https://gitnova.dev/en/r/zengshuangzi/mcd-money-saver ## Useful for - Find the cheapest order within a given budget - Auto-claim all available McDonald's coupons - Build a combo under a calorie limit with the biggest discount ## Why it’s here - Star-counter measurements on 2026-10-24 (UTC), 13:51–18:41: 123 → 145 stars (+22). This is the change over that interval. - Estimated end-of-day forecast: about +31 stars, using observed gains and the previous day. - The repository is 2 days old and already has 145 stars. With less than two weeks of history, there's no usual pace to compare the spike against yet. - Top new repositories this week: #169. - About 12 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: 19 - Issues and pull requests: 0 - Watchers: 0 - Average over the last week: 40 per day - Usual pace: too little history (under two weeks) - Stars in the last hour (measured): 12 ## Stars per day, last 3 days (oldest → newest, today is partial) 2026-10-22 … 2026-10-24: 0, 90, 22 ## Spotted in now - Top new repositories this week: #169 ## More in this category 1. **aicodeking/leanrea** — 6.3 · Peaking · AI agents · Python · +187 stars measured 2026-10-24, 00:03–18:41 UTC, ≈ 249 by evening An 8 KB skill file for AI agents that replaces the REA MCP server: it tells the agent which CLI tools (asar, otool, nm, jadx, Ghidra, etc.) to use for reverse engineering and how to avoid common traps. Per the author's benchmark it is 38%… Full card: https://gitnova.dev/en/r/aicodeking/leanrea.md 2. **NVIDIA/OpenShell** — 6.2 · Breakout · AI agents · Rust · +564 stars measured 2026-10-24, 00:03–18:41 UTC, ≈ 728 by evening A safe, private runtime for autonomous AI agents: isolated sandbox containers governed by declarative YAML policies restricting filesystem, network, and process access. Manages credential injection for agents like Claude, Codex, OpenCode,… Full card: https://gitnova.dev/en/r/NVIDIA/OpenShell.md 3. **makecindy/cindy** — 6.0 · Breakout · AI agents · TypeScript · +233 stars measured 2026-10-24, 11:41–18:41 UTC, ≈ 301 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. **JoasASantos/REA-Prompts** — 6.0 · Peaking · AI agents · +271 stars measured 2026-10-24, 00:03–18:41 UTC, ≈ 343 by evening A curated collection of prompts for using REA (Reverse Engineer Anything) with AI coding agents to inspect binaries, firmware, kernels, games, APKs, Electron apps and websites. Covers installation, feature tracing, cloning, vulnerability… Full card: https://gitnova.dev/en/r/JoasASantos/REA-Prompts.md 5. **google-gemini/gemini-cli** — 5.9 · Breakout · AI agents · TypeScript · +292 stars measured 2026-10-24, 11:39–18:41 UTC, ≈ 357 by evening Google's open-source AI agent that runs Gemini directly in the terminal: understands and edits code, answers questions about a repository and automates tasks. Supports MCP servers and a non-interactive mode for scripts. Full card: https://gitnova.dev/en/r/google-gemini/gemini-cli.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 2026-10-24 18:51 UTC, updated every 30 minutes.