# vxcn/mcd-kcal-picker > A Python skill that uses McDonald's China nutrition data via MCP to pick a meal combo matching a target calorie count under a cap, without placing orders. - Magnitude: 2.4 out of 10 — Steady - Stars: 157 total · +0 stars measured 2026-10-25, 15:52–17:16 UTC, ≈ 1 by evening - Star trust: star growth looks organic - Category: AI agents · Language: Python · Created: 2026-10-24 · Last push: 2026-10-24 - GitHub: https://github.com/vxcn/mcd-kcal-picker · Page: https://gitnova.dev/en/r/vxcn/mcd-kcal-picker ## Useful for - Pick a 600 kcal meal under a 700 kcal cap in demo mode - Exclude spicy items from the combo with the --avoid flag - Study a minimal read-only MCP client implementation ## Why it’s here - Star-counter measurements on 2026-10-25 (UTC), 15:52–17:16: 157 → 157 stars (+0). This is the change over that interval. - Estimated end-of-day forecast: about +1 stars, using observed gains and the previous day. - The repository is 1 day old and already has 157 stars. With less than two weeks of history, there's no usual pace to compare the spike against yet. - Top new repositories this week: #147. - About 18 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: 6 - Issues and pull requests: 0 - Watchers: 0 - Average over the last week: 10 per day - Usual pace: too little history (under two weeks) - Stars in the last hour (measured): 0 ## Stars per day, last 2 days (oldest → newest, today is partial) 2026-10-24 … 2026-10-25: 19, 0 ## Spotted in now - Top new repositories this week: #147 ## More in this category 1. **makecindy/cindy** — 7.9 · Breakout · AI agents · TypeScript · +594 stars measured 2026-10-25, 00:10–17:54 UTC, ≈ 785 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 2. **google-gemini/gemini-cli** — 7.2 · Breakout · AI agents · TypeScript · +336 stars measured 2026-10-25, 00:09–17:54 UTC, ≈ 466 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 3. **morganlinton/BeautifulRust** — 6.8 · Early signal · AI agents · Rust · +292 stars measured 2026-10-25, 00:12–17:54 UTC, ≈ 386 by evening A Claude Code plugin with a rust-best-practices skill that teaches Claude to write idiomatic, robust Rust. The skill loads automatically whenever a task involves Rust, cargo, crates, the borrow checker, clippy, or .rs files. Full card: https://gitnova.dev/en/r/morganlinton/BeautifulRust.md 4. **DenisSergeevitch/ex-ussr-kinship-research** — 6.7 · Early signal · AI agents · Python · +222 stars measured 2026-10-25, 13:46–17:54 UTC, ≈ 278 by evening A skill for AI agents (Codex, Claude Code) that turns them into a family-history researcher for the former USSR: church books, civil, military, repression and deportation records. It keeps registers, checks evidence and replies in the… Full card: https://gitnova.dev/en/r/DenisSergeevitch/ex-ussr-kinship-research.md 5. **JoasASantos/REA-Prompts** — 6.6 · Peaking · AI agents · +279 stars measured 2026-10-25, 00:10–17:54 UTC, ≈ 376 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 --- 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 2026-10-25 17:55 UTC, updated every 30 minutes.