Star velocity · weekly

GitHub trending repositories by snapshot date

Explore dated GitHub trending snapshots, compare star activity, and read repository profiles before choosing a project.

Latest weekly snapshot · September 28, 2026

  1. 1

    eternity4719/HowToLiveBetter : Life advice that logs what you spend, what you gain and how solid the evidence is

    HTML

    A Chinese guide of practical suggestions on health, money, scams and legal traps, from chronic disease and first aid to rent disputes and workplace compensation. Each entry records what you spend, what you get back and how strong the evidence is, citing only journal papers and official documents, with an online search page for quick lookups.

    +18,046
  2. 2

    debpalash/VoiceStudio : Try voice design, transcription and dubbing in one workspace

    Python

    A local audio workspace for voice design, transcription, dubbing and longer narrated projects. Useful for trying several speech workflows with your own material in one application, with engine choice and hardware determining the supported languages and output quality.

    +12,353
  3. 3

    Niko1221/Strata : A 125B-parameter model running on one gaming GPU, faster than you can read

    C++

    A one-click installer that runs Qwen3.8-Flash-Next, a 125-billion-parameter model that normally needs a server, on a single NVIDIA card with 12 to 24 GB of VRAM and 64 GB of RAM. It serves an OpenAI-compatible API on localhost, reports 60 to 95 tokens per second in its own measurements, accepts image input, and calibrates the engine to your PC.

    +10,144
  4. 4

    DietrichGebert/ponytail : Stop your AI turning a small fix into a new framework

    JavaScript

    A set of instructions that asks AI coding agents to reuse existing code and question whether a new abstraction is needed. Its rules also explicitly retain validation and error handling, useful when your agent keeps making a small task unnecessarily complicated.

    +7,940
  5. 5

    vectorize-io/hindsight : Agent memory with three operations: retain, recall, and reflect to keep learning

    Python

    An agent memory system organized around three operations: retain observations, recall them when needed, and reflect to keep what an agent knows up to date. Memory banks and mental models structure the knowledge, it runs as a Docker, pip or embedded Python service against 25+ LLM providers, and an MCP server plus a two-line LLM wrapper connect it to coding agents.

    +7,301

Read this weekly snapshot →

Latest daily snapshot · October 5, 2026

  1. 1

    eternity4719/HowToLiveBetter : Life advice that logs what you spend, what you gain and how solid the evidence is

    HTML

    A Chinese guide of practical suggestions on health, money, scams and legal traps, from chronic disease and first aid to rent disputes and workplace compensation. Each entry records what you spend, what you get back and how strong the evidence is, citing only journal papers and official documents, with an online search page for quick lookups.

    +2,235
  2. 2

    Niko1221/Strata : A 125B-parameter model running on one gaming GPU, faster than you can read

    C++

    A one-click installer that runs Qwen3.8-Flash-Next, a 125-billion-parameter model that normally needs a server, on a single NVIDIA card with 12 to 24 GB of VRAM and 64 GB of RAM. It serves an OpenAI-compatible API on localhost, reports 60 to 95 tokens per second in its own measurements, accepts image input, and calibrates the engine to your PC.

    +1,949
  3. 3

    DietrichGebert/ponytail : Stop your AI turning a small fix into a new framework

    JavaScript

    A set of instructions that asks AI coding agents to reuse existing code and question whether a new abstraction is needed. Its rules also explicitly retain validation and error handling, useful when your agent keeps making a small task unnecessarily complicated.

    +1,766
  4. 4

    lexmount/moli : A headless browser that renders pixels only when an agent asks

    Rust

    A headless browser built in Rust for AI agents that treats page structure, not pixels, as the default. Reading a page as Markdown or a semantic tree skips layout and painting entirely; geometry, screenshots and screencasts render on demand and are discarded afterwards. Drive it from the CLI, CDP, WebDriver Classic or BiDi.

    +1,502
  5. 5

    pbakaus/impeccable : Fix the samey SaaS look AI models keep generating

    JavaScript

    Design guidance for AI coding agents that keeps generated interfaces from falling into the same template look. One /impeccable init records durable product facts in PRODUCT.md, 24 shared commands cover shaping, critique, polish and motion, and 61 deterministic detector rules run in a CLI or browser extension without any model call or API key.

    +1,078

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How to read these rankings

Numbers come from GitHub's official stargazers/history endpoint: stars gained on each day of the window. GH Archive supplies candidates; every count is checked against GitHub. GhTrends compiles these rankings independently.

Projects are ordered by stars gained during the same time window, making changes in attention easy to compare. GitHub's own Trending page uses its separate ranking method.

Each list carries its snapshot date and records project activity at that time. New attention provides leads to investigate; review documentation, code and recent activity to assess quality, security and maintenance.

Open a daily or weekly snapshot for the full list, then read a repository profile for its license, setup requirements, and limitations. Check recent commits and issues in the upstream repository before adopting it.