# linshenkx/prompt-optimizer > An AI prompt optimization tool that helps write better prompts and get better model outputs. Available as a web app, desktop app, Chrome extension, and Docker deployment. - Magnitude: 3.3 out of 10 — Steady - Stars: 36,466 total · +10 stars measured 2026-10-05, 10:59–12:35 UTC, ≈ 51 by evening - Star trust: star growth looks organic - Category: Language models · Language: TypeScript · Created: 2025-02-12 · Last push: 2026-09-24 - GitHub: https://github.com/linshenkx/prompt-optimizer · Homepage: https://prompt.always200.com · Page: https://gitnova.dev/en/r/linshenkx/prompt-optimizer ## Useful for - Optimize a prompt and compare results before and after changes - Test a prompt template with variables in a multi-turn conversation - Generate an image from an optimized text prompt ## Why it’s here - Star-counter measurements on 2026-10-05 (UTC), 10:59–12:35: 36456 → 36466 stars (+10). This is the change over that interval. - Estimated end-of-day forecast: about +51 stars, using observed gains and the previous day. - GitHub Trending TypeScript today: #13, +153 stars. - About 14 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: 4,207 - Issues and pull requests: 334 - Watchers: 127 - Average over the last week: 77 per day - Usual pace: 88 per day - Stars in the last hour (measured): 10 - Latest release: v2.11.10 (2026-09-11) ## Stars per day, last 30 days (oldest → newest, today is partial) 2026-09-06 … 2026-10-05: 56, 82, 68, 79, 86, 68, 45, 74, 63, 100, 68, 95, 87, 108, 116, 111, 123, 85, 122, 86, 71, 88, 57, 59, 39, 72, 53, 100, 164, 10 ## Spotted in now - GitHub Trending TypeScript today: #13, +153 stars ## More in this category 1. **Niko1221/Strata** — 8.2 · Breakout · Language models · C++ · +1,613 stars measured 2026-10-05, 00:06–12:33 UTC, ≈ 3,024 by evening A C++ local inference engine that runs the 125B MoE model Qwen3.8-Flash-Next on a regular PC with one NVIDIA GPU (12-24 GB) and 64 GB RAM, exposing an OpenAI/Anthropic-compatible API on localhost. Full card: https://gitnova.dev/en/r/Niko1221/Strata.md 2. **StayLameBro/backburner** — 6.2 · Early signal · Language models · Python · +160 stars measured 2026-10-05, 00:06–12:33 UTC, ≈ 294 by evening A llama.cpp fork that plugs an iPhone into a Mac over USB-C and splits the work: the Mac runs layers 1-40, the iPhone runs 41-64 on its GPU, speeding up prefill and allowing context up to 196k-229k tokens. Aimed at people running… Full card: https://gitnova.dev/en/r/StayLameBro/backburner.md 3. **antirez/ds4** — 5.9 · Breakout · Language models · C · +91 stars measured 2026-10-05, 00:06–12:33 UTC, ≈ 196 by evening DwarfStar (ds4) is a native C inference engine for running a few specific large LLMs (DeepSeek V4 Flash/PRO, GLM 5.x, Qwen3.8 Flash Next) on Metal, CUDA and ROCm. Targets consumer hardware like MacBooks, DGX Spark and Strix Halo, with SSD… Full card: https://gitnova.dev/en/r/antirez/ds4.md 4. **empero-org/brewery-ai** — 5.2 · Early signal · Language models · Python · +24 stars measured 2026-10-05, 07:56–12:33 UTC, ≈ 58 by evening A console agent that walks users through the full fine-tuning cycle for language and image models via a chat with an AI guide: from picking a base model and data to training on a GPU and publishing to Hugging Face. Full card: https://gitnova.dev/en/r/empero-org/brewery-ai.md 5. **Edge0-AI/Edge0** — 4.9 · Breakout · Language models · Python · +199 stars measured 2026-10-05, 00:07–12:33 UTC, ≈ 344 by evening An open-source streaming MoE inference framework: expert weights are offloaded from SSD on demand while a trained prerouter predicts routing ahead of time. Runs on Apple Silicon via MLX and ships with two ready-to-run model tiers (35B and… Full card: https://gitnova.dev/en/r/Edge0-AI/Edge0.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 2026-10-05 12:40 UTC, updated every 30 minutes.