日报 · 2026-11-01
GitHub 新星 · 汇总昨日新收录项目
当日新增收录 44 个项目
覆盖日期：2026-11-01 · 北京时间
发布时间：2026/11/2 08:00:20
部分来源已不可公开，本期文章将按其余项目修订后重新展示。下方为已保存的项目资料。
本期项目资料
收录数按本期首次达标收录的项目统计。
- ComputerUseAgent/AutoCuaPython · 1,058 Stars
网页自动化、AI辅助编程、多账号切换
Stars 统计更新于 2026/11/2 07:51:20
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作者描述
Automate with computer-use agent (ComputerUse / CUA) for macOS, Windows, Linux, Browser, iOS & Android. It sees the screen, clicks, types, browses and writes the code too. One agent, every computer.
编报时的 AI 中文解读
AutoCua 是一个自动化计算机使用的多智能体框架，能够驱动桌面、浏览器、移动设备等完成点击、输入、浏览和编码等任务。适用于需要自动化操作各种软件和设备的开发者和高级用户。
编报时的 README 依据
**Full capabilities:** **[agent_capabilities.md](https://github.com/AutoCua/AutoCua/blob/main/agent_capabilities.md)** https://github.com/user-attachments/assets/03a9a5ab-5049-4911-b725-63792d1b6253 | | Windows | Linux | macOS | |:--|:--:|:--:|:--:| | **Computer use** — any desktop app, with real mouse and keyboard input | ✓ | ✓ | ✓ | | **Browser skills** — Chrome, Firefox, Edge, Brave and Opera | ✓ | ✓ | ✓ | | **Shell use** — a coding agent in a real terminal | ✓ | ✓ | ✓ | | **Web use** — your own Chrome, driven through the AutoCua extension | ✓ | ✓ | ✓ |
| **Mobile use** — an iOS Simulator, or your iPhone or iPad, over USB, or Wi-Fi in the app | — | — | ✓ | | **Mobile use** — an Android emulator, or your Android phone, over USB, or Wi-Fi in the app | ✓ | ✓ | ✓ | </div> --- ## Web agent: fast mode 6.1 seconds for a flight search. Agent mode: web. https://github.com/user-attachments/assets/8cc797d5-5556-40a9-bbfc-5d6aa8880fb8 ## Web agent: quality mode Under a minute for three tasks in one run: an iPhone 18 Pro into the Apple bag, a case into the Amazon basket, and a Google Sheet of Meta's five-year financials. Agent mode: web.
https://github.com/user-attachments/assets/82bf6163-55c9-4cc4-95e7-9c6466f2a25d ## iOS agent: iPhone use A paired iPhone, driven over the USB cable, or Wi-Fi in the app. Agent mode: mobile use, iOS. https://github.com/user-attachments/assets/3c22eb45-d939-4742-9053-22ecc75b416f --- ## Pick a surface One string decides what the agent drives. Everything else stays the same. ```python from AutoCua.agent_launcher import run_agent run_agent(mode="web use", provider="openrouter", model="gemini-3.8-flash", task="Open wikipedia.org and summarise today's featured article.") ```
<div align="center"> <img src="AutoCua/logo/autocua-bots.png" alt="AutoCua" width="820"/> <h1>AutoCua</h1> <h3>Automatic Computer Use Agent.<br/>Mac, Windows, Linux, real phone, simulator, any browser.<br/>A multi-agent harness engine.</h3> [](https://pypi.org/project/AutoCua/) [](https://pypi.org/project/AutoCua/)
or 15,000 characters, with `shell` keeping a 50-line tail, `view` capped at 2,000 lines and `grep` at 8 MB, so one wide search or noisy build log can never blow up the conversation. Run either directly. They start in their own workspace, so point them at an absolute path when the work is in an existing project: ```bash python -m AutoCua.mac.agent.coder --task "refactor the auth module in /Users/me/projects/api" --provider anthropic --model claude-sonnet-5
> Shipping it inside the wheel would make this project its distributor to every person who runs > `pip install`, which that licence does not allow for free. You receive it from its author. > See [THIRD_PARTY_NOTICES.md](https://github.com/AutoCua/AutoCua/blob/main/THIRD_PARTY_NOTICES.md). ### Linux, from pip The Linux wheel is built for x86_64 and needs a GNOME desktop (tested on Ubuntu with Wayland; X11 is not tested yet). The agent reads and drives the desktop through AT-SPI, GTK and the XDG RemoteDesktop portal. Those bindings come from your distro, not from pip, so install them once:
[](https://github.com/AutoCua/AutoCua/blob/main/README.md#the-browser-agent) [](https://github.com/AutoCua/AutoCua/blob/main/README.md#providers-and-models) <table><tr><td> ```bash pip install AutoCua ``` </td></tr></table> <sub>Windows 10 and 11 · Linux with GNOME · macOS on Apple Silicon or Intel</sub>
### Answering UAC prompts on Windows Windows' user-mode `SendInput` cannot deliver input to the UAC secure desktop, so an elevation prompt can only be answered from kernel mode. That is the one thing the [Interception](https://github.com/oblitum/Interception) driver does here. `pip install` cannot set it up, and no packaging trick changes that: a wheel is unpacked and never executed, pip does not run elevated, and the driver binds its input slots only when it loads **at boot**. Without it **every mode still works** — you simply lose UAC handling, and a
- alexgaoth/awesome-reverse-engineeredPython · 1,038 Stars
工具索引、Agent技能、MCP服务
Stars 统计更新于 2026/11/2 07:46:27
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作者描述
Don't reverse engineer it twice. 17,000+ open-source tools built by reverse engineering closed apps, APIs, devices, protocols, file formats, games and AI tools. Search site + agent skill + MCP server, refreshed nightly.
编报时的 AI 中文解读
这是一个收录了17,734个通过逆向工程实现的开源工具的索引，涵盖非官方客户端、驱动、文件格式解析、重实现等，并提供网站搜索、Agent技能和MCP服务器，方便用户查找和复用已有逆向成果。
编报时的 README 依据
When a task needs to talk to something with no official API (a smart plug, a car, a chat app, a file format), your agent searches this index, ranks by stars, activity and license, reads the README, and picks the right tool. ```bash npx skills add alexgaoth/awesome-reverse-engineered ``` <details><summary><b>Other ways to install</b></summary> **Claude Code plugin** ``` /plugin install reverse-engineered --marketplace alexgaoth/awesome-reverse-engineered ``` **MCP server (Claude Desktop, Cursor, any MCP client)** ```bash
**[Search the index](https://alexgaoth.github.io/awesome-reverse-engineered/)** or give it to your agent: `npx skills add alexgaoth/awesome-reverse-engineered` [](https://awesome.re) [](#whats-inside) [](.github/workflows/refresh.yml)
claude mcp add reverse-engineered -- uvx --from "git+https://github.com/alexgaoth/awesome-reverse-engineered#subdirectory=mcp" reverse-engineered-mcp ``` ```json {"mcpServers": {"reverse-engineered": {"command": "uvx", "args": ["--from", "git+https://github.com/alexgaoth/awesome-reverse-engineered#subdirectory=mcp", "reverse-engineered-mcp"]}}} ``` **Any agent or shell (one file, Python standard library only)** ```bash curl -sL https://raw.githubusercontent.com/alexgaoth/awesome-reverse-engineered/main/plugin/skills/find-reverse-engineered/scripts/re_index.py -o re_index.py
Unofficial APIs break when the vendor changes their side, so check health before you depend on a project. ## How it's built ```mermaid flowchart LR A[Research agents<br/>GitHub, HN, Reddit,<br/>awesome-lists] --> B[Scope filter<br/>interoperability only] B --> C[GitHub API check<br/>exists, stars, license] C --> D[(data/entries.json)] D --> E[README and<br/>category pages] D --> F[Search website] D --> G[Agent skill] H[Nightly refresh<br/>GitHub Action] -->|stars, archived,<br/>dead links| D ```
- Murea-Labs/InWorldPython · 1,029 Stars
视频生成、音频生成
Stars 统计更新于 2026/11/2 07:46:27
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编报时的 AI 中文解读
Murea-InWorld 是一个开源项目，提供从文本和参考图像生成带同步声音的视频，并包含一个智能体(Murea-Mind)将用户操作转化为连续的叙事视频。适用于创作者、游戏玩家及研究人员。
编报时的 README 依据
<!-- <img src="docs/assets/reference.gif" width="100%"> --> <b>🖼️ Film a scene from references</b><br> Two characters and a place, one prompt, a clip with dialogue and sound. <a href="inference/README.md#multi-reference-generation">Murea-Fast</a> </td> <td width="50%" valign="top"> <!-- <img src="docs/assets/continuation.gif" width="100%"> --> <b>🔄 Continue a clip</b><br> Pick up from the last frames and keep the action going. <a href="inference/README.md#continuation">Murea-Fast</a> </td> </tr> <tr>
<td width="50%" valign="top"> <!-- <img src="docs/assets/agent.gif" width="100%"> --> <b>🎭 Play a story</b><br> Type an action, watch it happen, choose what comes next. <a href="agent/README.md#quick-start">Murea-Mind</a> </td> <td width="50%" valign="top"> <!-- <img src="docs/assets/coop.gif" width="100%"> --> <b>👥 Play with friends</b><br> A shared room, one clip per round, with optional AI teammates. <a href="agent/README.md#co-op-mode">Co-op mode</a> </td> </tr> </table> <a name="how-it-fits-together"></a>
## 🧭 Where to start | I want to… | Start here | | --- | --- | | Play a story in the browser | [Murea-Mind quick start](agent/README.md#quick-start) | | Play with friends | [Co-op mode](agent/README.md#co-op-mode) | | Generate or continue a clip from the command line | [Murea-Fast quick start](inference/README.md#quick-start) | | Call the model from my own code | [API reference](inference/docs/api.md) | | Run the service on my GPUs | [Deployment](inference/docs/deployment.md) | | Know how fast it is and how much memory it needs | [Performance](inference/docs/performance.md) |
| Interface | HTTP API, command line | Web UI, terminal, Python API | <a name="quick-start"></a> ## 🚀 Quick start **1. Start Murea-Fast on a GPU machine.** Install the environment and the LTX-2.5 base components as described in [Deployment](inference/docs/deployment.md), download the [murea-fast.safetensors checkpoint](https://huggingface.co/MureaLabs/InWorld/blob/main/murea-fast.safetensors), and set the four paths in `inference/configs/single-gpu.json`. Set `checkpoint` to the absolute path of the downloaded file. Then: ```bash cd inference
| Contribute | [CONTRIBUTING.md](CONTRIBUTING.md) | <a name="components"></a> ## ⚙️ Components | | [Murea-Fast](inference/README.md) | [Murea-Mind](agent/README.md) | | --- | --- | --- | | What it is | Inference service for an 8-step distilled derivative of LTX-2.5, on a pinned SGLang | Web app and Python package: a language-model director, deterministic checks, world memory and a critic | | Runs on | Linux and NVIDIA GPUs with CUDA. Verified on one H20 and on four H20s | Any machine with Python 3.12; needs a language and image model API key and a Murea-Fast service |
bash scripts/murea-fast prepare --config configs/single-gpu.json bash scripts/murea-fast start --config configs/single-gpu.json curl --fail http://127.0.0.1:30260/health ``` **2. Run Murea-Mind on any machine.** It needs [uv](https://docs.astral.sh/uv/) and a key for text and images (Gemini, any OpenAI-compatible server, or DashScope): ```bash git clone https://github.com/Murea-Labs/InWorld.git Murea-InWorld && cd Murea-InWorld/agent cp .env.example .env # set GEMINI_API_KEY and MUREA_URL=http://<gpu-host>:30260 ./run.sh # then open http://127.0.0.1:8080 ```
│ └── vendor/sglang/ pinned SGLang with the model implementation └── agent/ Murea-Mind ├── murea_agent/ the agent (Python package) ├── app/ FastAPI server ├── frontend/ React UI (prebuilt in frontend/dist) ├── docs/ co-op mode design notes └── tests/ ``` <a name="security"></a> ## 🔒 Security Neither the inference service nor the agent has authentication. Read [SECURITY.md](SECURITY.md) before deploying them on a shared network. <a name="contributing"></a> ## 🤝 Contributing
see [Provenance](inference/docs/provenance.md) for details. The agent calls third-party language and image model APIs, which have their own terms. <a name="citation"></a> ## 📚 Citation ```bibtex @misc{murea_inworld2026, title = {InWorld: From Imagination to Living Worlds with Agents and Fast Video Generation}, author = {{Murea Labs}}, year = {2026}, url = {https://murea.ai/page/paper/InWorld-technical-report.pdf} } ``` <a name="contact"></a> ## ✉️ Contact Email: [labs@murea.ai](mailto:labs@murea.ai)
- storytold/craft-anythingRust · 937 Stars
软件逆向分析、AI辅助编程
Stars 统计更新于 2026/11/2 07:30:44
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作者描述
Craft Anything: understand how any software works, and craft your own.
编报时的 AI 中文解读
Craft Anything 是一款开源工具，能分析网站、应用或游戏的工作原理，并借助 AI 编码代理重建类似项目。它提供桌面应用、命令行和 MCP 服务，适合希望逆向工程并复刻软件的用户。
编报时的 README 依据
## Two ways to use it - **Simple** (default): "What do you want to make?" Pick a website, app or game, describe it, press Start. A project page shows the four steps (Study → Build → Check → Ready), what the agent is doing in plain words, question and approval cards, how alike the result is, and buttons to open the result or its folder. Ask for changes in the box at the bottom. "Just look inside" opens a target for questions without building anything (in Deep mode). - **Advanced**: the full workbench: every tool (Ctrl/Cmd+K), functions, strings, pseudo-C,
never sees or handles your account. Your use of it falls under your own agreement with Anthropic. See [docs/claude-code.md](docs/claude-code.md) for how and why. A Codex adapter exists but hasn't been verified on a real install yet. Anthropic, OpenAI, OpenRouter and local OpenAI-compatible servers are available for questions and analysis (Settings → AI). ## Built for agents Every tool is also a CLI subcommand and an MCP tool, so an agent can study a target or run a whole rebuild without the app: ```sh craft-anything-cli commands # every tool, by toolset
setup layers) for native programs, .NET, Java, Android, Apple, Electron/JavaScript, websites, firmware, packet captures, databases and game files. Its own decoders, disassembler and decompiler work without any outside program; Deep mode uses them all, and Ghidra when it's installed. It powers the desktop app (egui), the CLI and the MCP server, and parts of it run in the browser as WebAssembly. The full list is in [docs/tools.md](docs/tools.md). ## Get started Requires Rust **1.97 or newer** (a dependency needs it; `rustup update`). On Debian or Ubuntu, the desktop app also needs: ```sh
<img src="docs/images/workbench.png" alt="The Advanced workbench: a function list, pseudo-C of the selected function, the agent answering a question with a tool call, and the evidence ledger" width="100%"> <br> <sub><b>Advanced:</b> functions, pseudo-C, the agent and the evidence behind every answer.</sub> </p> ## AI Building needs a coding agent on your computer. **Claude Code** is supported first: Craft Anything runs your own, unmodified `claude` program, which uses your own sign-in; Craft Anything
remember the answer). Settings → General also lists projects from more folders; removing one only takes it off the list. ## Status > [!IMPORTANT] > **Status:** Craft Anything is in early alpha. What works today, what is partial and what's next: > > - **Works today:** the desktop app (Simple and Advanced), the CLI and the MCP server; the > Study → Build → Check → Refine workflow for websites, apps and games with Claude Code as the > builder; website checks at three screen widths; game rebuilds in Unity, Unreal or Godot; Deep
> mode with Ghidra; generated pictures and 3D models (opt-in, your own fal.ai key); plugins (MCP > servers, and WASM components in builds with the `wasm-plugins` option). > - **Partly there:** building with API keys and other coding agents (built, not yet run live), > behaviour checks for apps and games, a few engine tools tested only against stand-ins. > - **Next:** the first public release (installers for Windows, macOS, Linux and FreeBSD, and the > browser viewer are set up in CI), then the managed tier. >
- hyz317/HairDeckPython · 589 Stars
头发建模、动画生成、VRM导出
Stars 统计更新于 2026/11/2 07:30:47
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作者描述
HairDeck: Animation-Ready Stylized Hair Cards from a Single Image
编报时的 AI 中文解读
HairDeck 是一个从单张图像生成风格化头发卡片及其弹簧骨骼链的研究项目，输出可用于动画的 GLB 或 VRM 模型，并提供在线演示和本地界面。
编报时的 README 依据
[configs/paths.example.json](configs/paths.example.json) and [hairdeck/paths.py](hairdeck/paths.py). <a name="quick-start"></a> ### 🚀 Quick start Generate four variations from a character image, then export variation 0 as a VRM avatar and a head-turn video: ```bash python scripts/image_to_hair.py character.png --out results/my_character --n 4 python -m hairdeck.vrm.export results/my_character/character 0 ``` Results are written to `OUT/<image name>/`, here `results/my_character/character/`.
`--n` accepts 1–4 variations; `--seed` sets the first seed. Use `--no-chains` to generate cards only. For custom models, pass `--ckpt` and a matching `--chain_ckpt` trained with the same card VAE. <a name="local-demo"></a> ### 🖼️ Local demo ```bash python -m pip install -r requirements-demo.txt python demo/app.py --port 7860 ``` Open [http://127.0.0.1:7860](http://127.0.0.1:7860) to generate hair, inspect variations, and export a VRM or animation preview. You can also try the [hosted demo](https://huggingface.co/spaces/hyz317/HairDeck). <a name="outputs"></a> ## 📦 Outputs
[🛠️ Installation](#installation) · [🤗 Model weights](#model-weights) · [🚀 Quick start](#quick-start) · [🖼️ Local demo](#local-demo) · [📦 Outputs](#outputs) · [📊 Evaluation](#test-set-evaluation) · [🏋️ Training](#training) · [📝 Citation](#citation) <a name="installation"></a> ### 🛠️ Installation Use Linux x86-64, Python 3.12 and one NVIDIA CUDA GPU. The release was tested with PyTorch 2.8 and CUDA 12.8. The video preview also needs `ffmpeg` on your `PATH`. ```bash git clone https://github.com/hyz317/HairDeck.git cd HairDeck python -m pip install -r requirements.txt
python -m pip install --no-deps pyrender==0.1.45 # without its old PyOpenGL pin ``` Run the commands below from the repository root, in the same Python environment. <a name="model-weights"></a> ### 🤗 Model weights Our checkpoints and supporting assets are hosted at [hyz317/HairDeck](https://huggingface.co/hyz317/HairDeck). SAM 3 and DINOv3 are gated: first accept their licences on [facebook/sam3](https://huggingface.co/facebook/sam3) and [facebook/dinov3-vitl16-pretrain-lvd1689m](https://huggingface.co/facebook/dinov3-vitl16-pretrain-lvd1689m), then log in: ```bash hf auth login
python scripts/setup/download_weights.py --only dora test_data charm_test_pc python scripts/data.py DATASET_DIR VRM_DIR bash scripts/train/launch_vae.sh bash scripts/train/launch_pc_dit.sh && bash scripts/train/launch_img_dit.sh && bash scripts/train/launch_chain_dit.sh ``` The launchers write to `ckpt/train_*`, separately from the downloaded checkpoints. The current image-training recipe includes synthetic appearance augmentation; the restyled-render pool used for the released image model is not included in this release. <a name="citation"></a> ## 📝 Citation ```bibtex
- emanuele-em/kanzoRust · 585 Stars
任务管理、AI辅助编程
Stars 统计更新于 2026/11/2 07:36:41
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作者描述
Self-hosted, sharable kanban for humans and agents. One 4.5 MB binary, 4.5 MB of RAM, 10 to 60 tokens per agent reply, starts in 2 ms, zero setup.
编报时的 AI 中文解读
Kanzo 是一个自托管的看板应用，同时提供 MCP 服务器，让人类用户和编码代理可以共同管理任务。它占用资源极低，通过 git 实现多设备同步，无需账号或服务器。
编报时的 README 依据
| `kanzo` | Starts the board at http://localhost:4242 and opens it; `--port` for another port, `--no-open` to not open it | | `kanzo service install` | Keeps the board running and starts it at login; `uninstall` removes it | | `kanzo mcp` | The MCP server for agents: they start it, not you | | `kanzo sync` | Commits the board and pulls or pushes it; `--repo <url>` sets the repo, `--keep-local` or `--keep-remote` when both sides changed | | `kanzo export` | Prints the board as Markdown; `-f json` for JSON, `-p <project>` for one project, `-o <file>` to save it |
Paste or drop an image into a task or a comment to attach it, as in ChatGPT. Agents get its file path and can open it. When a new version is out, the sidebar offers it: one click installs it and restarts the board. ## Connect your agents ```sh claude mcp add kanzo --scope user -- kanzo mcp # Claude Code codex mcp add kanzo -- kanzo mcp # Codex ``` Other MCP clients: run `kanzo mcp` (apps like Raycast need the full path, from `which kanzo`), or use the running board at `http://localhost:4242/mcp`.
## Install ```sh curl -LsSf https://github.com/emanuele-em/kanzo/releases/latest/download/kanzo-installer.sh | sh ``` For macOS and Linux, including every Raspberry Pi. On Windows, in PowerShell: ```powershell powershell -ExecutionPolicy Bypass -c "irm https://github.com/emanuele-em/kanzo/releases/latest/download/kanzo-installer.ps1 | iex" ```
Everything lives in `~/kanzo`: the board in `kanzo.db`, settings in `config.toml`. Use another folder with `--home` or `KANZO_HOME`. ```toml port = 4242 listen = "127.0.0.1" # "0.0.0.0" opens the board to your network: no logins, so only on one you trust mcp_http = true # MCP at /mcp ``` ## Small and fast | | | | --- | --- | | Program | 4.1 MB, SQLite included | | Memory | 4.5 MB idle, 8 MB with 3,000 tasks | | Start | 2 ms | | Board of 3,000 tasks | 17 ms to load in the browser | | Agents' tool list | about 900 tokens, once per session |
- speridlabs/idol-sdkPython · 505 Stars
3D模型生成
Stars 统计更新于 2026/11/2 07:36:28
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作者描述
Idol: a single image to 3D Gaussians. Inference SDK and demo.
编报时的 AI 中文解读
Idol 是一个将单张物体图片转换为 3D 高斯泼溅模型的工具，提供推理 SDK 和演示。它适用于需要从单张图片快速生成 3D 模型的开发者或研究人员。
编报时的 README 依据
## Inference ```bash python -m idol.sample --image photo.jpg --mode real python -m idol.sample --image renders/ --mode synthetic --out outputs ``` For each image this writes `<name>.ply` (open it in any Gaussian splat viewer), `<name>_input.png` (the image the model saw, after background removal and cropping) and `<name>_camera.json` (the predicted camera of the input). **Pick the mode for your input:** | `--mode` | for | |---|---| | `synthetic` (default) | computer generated images| | `real` | real world photographs | Other flags: | flag | default | | |---|---|---|
**Faster sampling is on by default on GPU** The first image in a process is slower while it pytorch compiles; the rest run at full speed. ### Python API ```python from idol import IdolPipeline pipeline = IdolPipeline.from_pretrained("speridlabs/idol") output = pipeline("photo.jpg", mode="real", seed=42, num_gaussians=1_048_576) output.gaussian.save_ply("photo.ply") output.preprocessed_image.save("photo_input.png") ``` ### Demo The Gradio app behind the [Hugging Face Space](https://huggingface.co/spaces/speridlabs/idol) is in `demo/`,
[demo](https://huggingface.co/spaces/speridlabs/idol) has 93 more examples ready to run and takes your own images as well. ## Model | | | |---|---| | Output | 3D Gaussians: 32,768 to 1,048,576 (default 262,144), standard 3DGS `.ply` | | DiT | 370M parameters | | Image conditioning | DINOv3 ViT-H+ and FLUX.2 VAE | | Decoder | 288M parameters | | Background removal | BiRefNet | | Sampler | Euler, 50 steps, classifier-free guidance 3.0, time shift 3.0 | ## Install ```bash pip install -e . # Python >= 3.10, PyTorch >= 2.5
pip install -e ".[demo]" # + Gradio, to run the demo locally ``` The weights are downloaded from Hugging Face on first use, you need to request access to [facebook/dinov3-vith16plus-pretrain-lvd1689m](https://huggingface.co/facebook/dinov3-vith16plus-pretrain-lvd1689m) and [black-forest-labs/FLUX.2-dev](https://huggingface.co/black-forest-labs/FLUX.2-dev) first, then log in with `hf auth login`. `flash-attn`, if installed, is used for attention; otherwise PyTorch's `scaled_dot_product_attention` is (same result, slower). Set `ATTN_BACKEND=sdpa` or `ATTN_BACKEND=flash_attn` to choose.
- Centiplatrap/pc-game-fps-doctorJavaScript · 489 Stars
游戏性能诊断、游戏问题修复、性能对比测量
Stars 统计更新于 2026/11/2 07:30:47
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作者描述
One button: why the game stutters, why it lags and why it won't start. Pitstop measures with PresentMon, explains in plain words, fixes Windows only, and undoes every change in one click.
编报时的 AI 中文解读
Pitstop 是一款面向 Windows 玩家的免费工具，用于诊断和修复游戏无法启动、卡顿、掉帧和网络延迟问题。它通过一键检查、一键修复和一键撤销，帮助玩家快速定位并解决常见性能问题，并生成可分享的对比卡片。
编报时的 README 依据
<img src="assets/pitstop.gif" alt="Check my PC finds 4 things slowing the PC down. Fix all sets the monitor to 165 Hz and waits while the screen cable and a network cable are plugged in. Measured again, the same PC goes from 118 to 231 FPS" width="880"> </p> <h3 align="center">Fix VAN 1067, FPS drops and lag in VALORANT. Free, in about a minute.</h3> Your game won't start, stutters or lags? Pitstop finds out why in about a minute and fixes what it can, with one-click undo. It never touches the game, Vanguard or Windows security. ## Download | System | File | | |---|---|---|
| Windows 10 and 11 | [`Pitstop-1.2.1-portable-x64.exe`](https://github.com/Centiplatrap/pc-game-fps-doctor/releases/latest) | One file. No installer, no admin rights | > [!NOTE] > The build isn't code-signed yet, so SmartScreen may warn you the first time. Choose **More info**, then **Run anyway**. ## How to use 1. Open Pitstop and press **Check my PC**. 2. Press **Fix all**. Pitstop shows you how to do the rest. 3. Press **Measure again** and share your before and after. ## What it fixes ### Won't start
<summary><b>Can Pitstop get me banned?</b></summary> No. Pitstop never touches the game, its files, Vanguard or its driver. It changes Windows settings you could change yourself, and logs each one so it can be undone. </details> <details> <summary><b>How many FPS will I gain?</b></summary> Nobody can promise a number. Pitstop finds what's holding your PC back and measures before and after. If nothing is wrong, it says so. </details> <details> <summary><b>I got VAN 152. Can Pitstop fix it?</b></summary>
No. VAN 152 is a hardware ban, typically about 4 months, and no tool can lift it. "HWID spoofers" get the PC banned again. If you have questions, submit a ticket to Riot support. </details> <details> <summary><b>Will it turn off security features to make the game run faster?</b></summary> Never. On Windows 11, Vanguard needs TPM 2.0 and Secure Boot, and may ask for Memory integrity and IOMMU. Pitstop helps you turn them on. Riot says enabling IOMMU has a negligible performance impact. </details> <details> <summary><b>Is the ping the same as in the game?</b></summary>
- arpanjot-coding/AVaultKotlin · 488 Stars
通话录音、加密存储
Stars 统计更新于 2026/11/2 07:30:47
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作者描述
AVault - Call Recorder (No Root Required) | Privacy-first, hardware-encrypted audio vault for Android 12-16+. Rootless call recording via Shizuku with AES-256-GCM, biometrics & auto-cleanup.
编报时的 AI 中文解读
AVault 是一款面向 Android 12 至 16+ 设备的开源通话录音与加密音频保险库应用，无需 root，利用 Shizuku 实现免root通话录音，并采用硬件级 AES-256-GCM 加密保护录音文件。适合需要在合规前提下安全保存通话记录的个人用户。
编报时的 README 依据
adb shell sh /sdcard/Android/data/moe.shizuku.privileged.api/start.sh ``` 3. Shizuku will confirm **"Shizuku is running"** with version and API level. ### Authorizing AVault 1. Launch **AVault**. 2. When prompted on the onboarding or dashboard screen, tap **"Authorize"** on the Shizuku permission dialog. 3. AVault binds immediately to the background daemon via Android Binder IPC. --- ## 📊 System Architecture & Data Flow Diagrams ### 1. End-to-End Audio Capture & Encryption Pipeline ```mermaid flowchart TD
Trigger["Periodic Retention Worker\n(Executes on App Start & Daily Alarm)"] --> CheckEnabled{"Auto-Delete Retention\nPolicy Active?"} CheckEnabled -- Disabled --> KeepAll["Retain All Records\n(Storage Untouched)"] CheckEnabled -- Active --> ReadConfig["Read Retention Horizon\n(1d, 7d, 14d, 30d, 60d, 90d, 180d, 1y)"] ReadConfig --> ScanRecords["Query All Encrypted .vault Containers"] ScanRecords --> RecordLoop{"Iterate Each Container"} RecordLoop --> CheckBookmark{"Is Recording\nBookmarked ('Saved')?"}
- **Git:** Version 2.30+ - **Java Development Kit (JDK):** Version 17 or 21 (Eclipse Temurin or OpenJDK recommended) - **Android SDK:** Platform API 36 (`android-36`), Build-Tools `36.0.0` - **Android Device:** Android 12 (API 31) through Android 16+ ### Step-by-Step Instructions 1. **Clone Repository with Submodules:** ```bash git clone --recurse-submodules https://github.com/arpanjot-coding/AVault.git cd AVault ``` 2. **Configure Local SDK Path:** Create a `local.properties` file in the project root if not automatically configured: ```properties
## ⚡ Shizuku Rootless Privilege Provider Setup AVault relies on **[Shizuku](https://shizuku.rikka.app)** to communicate with privileged Android OS system services (`android.permission.CAPTURE_AUDIO_OUTPUT`, `android.permission.MANAGE_ONGOING_CALLS`) without rooting the handset. ```mermaid flowchart TD UserPhone["Android Handset\n(Android 12 – 16+)"] --> DevOpt["Enable Developer Options\n& Wireless Debugging"] DevOpt --> ShizukuApp["Launch Shizuku App"] subgraph Pairing Method ShizukuApp -->|Method A| WPair["Wireless Debugging Pairing\n(Enter 6-digit PIN on-device)"]
src="https://img.shields.io/github/stars/arpanjot-coding/AVault?style=social" height="20" style="height: 20px; max-height: 20px;" alt="GitHub Stars" /></a></p> --- ## ⚠️ Critical Academic & Security Research Notice > [!WARNING] > ### STRICTLY FOR ACADEMIC, SECURITY, AND EDUCATIONAL RESEARCH PURPOSES ONLY > > **LIMITATION OF LIABILITY & INDEMNIFICATION:**
> - **Wiretapping & Telecommunications Compliance:** Laws regarding recording telephone calls and intercepting digital communications differ significantly across sovereign nations, states, and provinces. Jurisdictions may enforce **one-party consent** (e.g., 18 U.S.C. § 2511 in the United States) or **all-party consent** (e.g., California Penal Code § 632, Germany StGB § 201, and GDPR Article 6).
- benjitaylor/skillsTypeScript · 474 Stars
AI辅助编程、图像编辑
Stars 统计更新于 2026/11/2 07:36:28
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作者描述
Skills for AI coding agents.
编报时的 AI 中文解读
为AI编码代理提供设计、动效相关技能的合集，包含用于生成产品UI示例的Stageshow技能。
编报时的 README 依据
# Skills Skills I use with coding agents for design and motion work. ## Stageshow  Helps your agent make faux product UI that looks like the real product: stills, feature cards, cursor demos and bento grids, built in React. It includes guidance on composition and motion, a kit to copy from, examples, and tools that film the result so the agent can check its work. ```sh npx skills add benjitaylor/skills --skill stageshow ```
- wanghao-SunSky/cs329z-chineseHTML · 386 Stars
AI智能体学习
Stars 统计更新于 2026/11/2 07:36:28
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作者描述
斯坦福 Stanford CS329Z Engineering AI Agents 中文教程：面向 Python 开发者的 AI 智能体课程，19 讲与 4 项实践，涵盖 LLM、RAG、工具调用、记忆、多智能体、评测与安全。完整 Markdown、在线与离线 HTML。Chinese course notes.
编报时的 AI 中文解读
面向Python开发者的AI智能体中文自学教程，基于斯坦福CS329Z公开材料，涵盖LLM、RAG、工具调用、记忆、多智能体、评测与安全，包含19讲和4项实践练习。
编报时的 README 依据
| 19 讲中文教程 | [从第 1 讲开始](01-Agent基础与全景.md) | | 从零搭建 Agent、设计评测、课程项目、论文实践 | [实战练习](exercises/) | | HW1 与第 5 讲配套代码的阅读指南 | [代码导读](code-guide.md) | | 支持搜索、目录、深浅主题的网页，以及单文件离线版 | [HTML 文件](html/) | 适合会写 Python、了解基本 API 调用，希望系统学习 Agent 开发的读者。建议先读第 1–4 讲，再结合 HW1 动手实践；完整路线见课程目录。 ## 本地阅读与构建 下载仓库后，直接用浏览器打开 `html/index.html`。只想保存一个文件，可以使用 `html/offline.html`。 修改 Markdown 后，在仓库目录运行（需要 Node.js 18+ 和 Python 3）： ```bash node tools/build_site.mjs python3 tools/verify_publication.py ``` ## 来源与修订
- ShineFinancialStrut/game-server-route-racerRust · 351 Stars
游戏加速
Stars 统计更新于 2026/11/2 07:30:47
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作者描述
Detour times every route to your game server, puts only the game's traffic on the fastest one, and says so plainly when no route can help. Free relays: your own or the community's.
编报时的 AI 中文解读
Detour 是一款免费的游戏网络加速工具，通过为游戏流量寻找更快的网络路径来降低延迟，并明确告知用户何时无法优化。适用于希望改善在线游戏体验的玩家。
编报时的 README 依据
<h3 align="center">A free ExitLag alternative. Finds a faster route to your game server, or tells you why none exists.</h3> Detour lowers your ping in online games. It finds a faster path to the game server and sends only your game through it. When no path can help, it tells you why instead of selling you one. It's free, with no account, no ads and no telemetry. ## Download | System | File | | |---|---|---| | Windows 10 and 11 | [`Detour-1.1.2-portable-x64.exe`](https://github.com/ShineFinancialStrut/game-server-route-racer/releases/latest) | One file. No installer, no admin rights |
Detour races your normal path against faster ones and keeps the winner, checking again every few seconds. Here, VALORANT's ping to Paris drops from 74 to 46 ms. ### No more lag spikes <p align="center"> <img src="assets/details.png" alt="Show details: the path race table, and a minute of ping with 11 lag spikes on the normal path and none with Detour" width="100%"> </p> Every packet travels two ways at once, so one lost on the way no longer turns into a spike. Lag spikes went from 11 a minute to none. ### An honest answer <p align="center">
> [!NOTE] > The build isn't code-signed yet, so SmartScreen may warn you the first time. Choose **More info**, then **Run anyway**. ## How to use 1. Start Detour, then start your game. Detour picks it up on its own. 2. Press **Lower my ping**. 3. Play. ## What it does ### A faster path, found for you <p align="center"> <img src="assets/main.png" alt="VALORANT is running. Ping 74 to 46 ms: a faster path found through Frankfurt. Grey line for the normal path, orange line for Detour's path" width="100%"> </p>
5. **Verdict.** Wi-Fi, bufferbloat and background downloads are checked first, because no path fixes them. CS2, Dota 2 and Deadlock already ride Valve's relay network, so Detour stays off for them. **Relays.** The community list ([`relays.toml`](relays.toml)) is signed, and every relay runs [`detour-relay`](crates/detour-relay/src/main.rs). A relay forwards only UDP, only to the one game-server address a client registered, rate-limited. It refuses private addresses and ports below 1024, so it can't be used as an open proxy or for web traffic. That's why volunteers can run one safely.
CS2, Dota 2 and Deadlock already route through Valve's own relay network, so a better path is rare. Detour tells you so and stays off. The same goes for any game where your normal path already wins the race. </details> <details> <summary><b>Does my own server really cost nothing?</b></summary> Yes, on Oracle Cloud's Always Free tier. Oracle asks for a card to verify you at sign-up, and Always Free resources stay free after the trial ends. The relay uses a sliver of one Arm core and far less than the free 10 TB of outbound data a month. </details> <details>
- Mieksido/surfcoreJavaScript · 351 Stars
QQ聊天、B站互动、记忆管理
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编报时的 AI 中文解读
SurfCore 是一个为 DeepSeek Harness（DSH）agent 提供身份与多平台交互能力的插件系统，将 agent 接入 QQ 和 B站，并支持可选的桌宠和语音，运行在 Windows 本机。适用于希望将 DSH agent 用于社交互动的开发者和用户。 安装需要 Windows、Node.js ≥22.13 和 DSH 0.2.1-rc.2 或更新版本，必须从仓库根目录安装，并需手动配置 SnowLuma（第三方 QQ 运行时）。 提供记忆卡、人格角色、主动搭话、白名单安全控制等功能，数据仅存于本地，不包含真实数据。
- caru-ini/stack-diagramPython · 339 Stars
架构图生成
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作者描述
Agent skill: describe your stack in a sentence, get an architecture diagram with official logos
编报时的 AI 中文解读
这是一个Agent Skill，用户用一句话描述技术栈，即可生成带有官方Logo的架构图。适用于使用支持Skills的AI编程助手（如Claude Code、Codex、Cursor）的开发者，快速可视化项目架构。
- yetone/alma-relayJavaScript · 322 Stars
远程访问
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作者描述
Self-host the relay for Alma Remote Access — control your desktop Alma from your phone, anywhere. Docker or Cloudflare Workers.
编报时的 AI 中文解读
自托管中继服务，用于 Alma 远程访问，让手机上的 Alma 应用能控制桌面上的 Alma，无需端口转发或 VPN。
- jyotipmahes/ML-Interview-PrepJupyter Notebook · 284 Stars
面试准备、算法实现
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- zortos293/EglantineC++ · 275 Stars
Switch2模拟器、运行游戏
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- SparrowPortray/horizon-free-capesJavaScript · 233 Stars
游戏装饰
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作者描述
Every cape, wing, hat, pet and emote in Drip is free: 24 capes, your own PNG or GIF cape, squad capes for your crew and emotes on the B wheel. Made for Horizon, no account.
编报时的 AI 中文解读
Drip 是一款专为 Horizon 客户端设计的免费装饰插件，提供各种披风、翅膀、帽子、宠物和表情，所有玩家无需账号即可使用。用户可以通过简单点击穿戴，或上传自己的图片/GIF制作动画披风。
- Verlintas/NOIRKotlin · 227 Stars
隐私审计、权限分析、数据流分析
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作者描述
手机隐私审计：用 adb 扫出 Android 应用的权限、上报端点与数据流向，并给出可回滚的处置。Desktop Android leak audit: permissions, endpoints, data flows, reversible fixes.
编报时的 AI 中文解读
NOIR 是一款运行在电脑上的 Android 隐私审计工具，通过 adb 读取设备的应用清单、权限和 APK 中的网络端点，生成风险评分和可执行的处置建议。适用于对自己设备进行安全审计的用户。
- RatioGoldsmithMuse/valorant-fps-lag-fixerRust · 226 Stars
游戏性能诊断、FPS优化、网络延迟检测
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作者描述
VALORANT won't start, stutters or lags? Tick reads the Vanguard code, measures FPS for 60 seconds, finds where the lag starts and fixes what it can, with one-click undo. Never touches the game.
编报时的 AI 中文解读
Tick 是一款面向 VALORANT 玩家的免费 Windows 工具，用于诊断游戏无法启动、FPS 下降和网络延迟问题，并提供一键修复和撤销功能。
- UpperSupervisor/horizon-modpack-compatibilityRust · 205 Stars
模组兼容查询、模组安装、模组追踪
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作者描述
Drop your mods folder, a Prism or MultiMC instance or an .mrpack on Hopper and it answers what Horizon already does, what has a port and what is not there yet, then installs the rest.
编报时的 AI 中文解读
Hopper 是供《我的世界》Horizon 玩家查询模组兼容性的桌面工具：输入模组名称或拖入模组包，即可获知模组在 Horizon 中是否已内置、已移植、可直接运行或尚未支持，并可一键安装可用模组、追踪未支持模组的动态。
- Ceilingpiintensify/horizon-mod-checkerRust · 195 Stars
模组兼容检查、一键安装、投票追踪
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作者描述
Is my mod on Horizon? Type a name or drop your whole pack and every mod gets one plain answer: built in, ported, works or not yet. What works installs in one click.
编报时的 AI 中文解读
Wanted 是一个桌面工具，用于检查 Minecraft Java 版模组是否能在 Horizon（Rust 重写版）上运行，并支持一键安装兼容模组。
- tavern-labs-ai/persona-ai-sdkTypeScript · 192 Stars
AI角色构建、记忆管理、模型接入
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作者描述
Persona AI SDK: default personas, durable character memory, and Bedrock/OpenAI adapters in one package.
编报时的 AI 中文解读
TypeScript SDK，用于构建具有持久记忆和预设人设的AI角色应用，提供人设卡片、记忆运行时及OpenAI/Bedrock模型适配器。
- ManufacturingSaw/horizon-capes-skins-minecraftJavaScript · 191 Stars
游戏外观定制、团队披风制作
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作者描述
Free capes, wings, hats, shoulder pets and emotes for Horizon, the Rust rewrite of Minecraft. Pick a piece, press Wear it, and everyone with Tailor sees it. No account, no shop.
编报时的 AI 中文解读
Tailor 为 Horizon（用 Rust 重写的 Minecraft Java 版 26.3）提供免费外观装饰，包括披风、翅膀、帽子、肩宠和表情。用户可穿戴这些外观，其他同样使用 Tailor 的玩家在任何服务器上都能看到。无需账户，完全免费。
- amirmushichge/pixel-playsHTML · 187 Stars
在线游戏
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作者描述
Small browser games as isometric pixel dioramas. No build step, no dependencies.
编报时的 AI 中文解读
这是一个包含多款小型浏览器游戏的合集，每款游戏以等距像素立体模型呈现，使用纯JavaScript编写，无需构建步骤或依赖。适合喜欢休闲小游戏的玩家在线游玩。
- mromidev/claude-animated-shortsTypeScript · 177 Stars
动画短片制作、视频渲染
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作者描述
Free Claude skill: viral animated story shorts (2D characters in a 3D world) with three.js + Remotion
编报时的 AI 中文解读
这是一个Claude技能，用于制作55-70秒的竖屏动画故事短片，采用2D角色在3D世界中的风格，通过three.js和Remotion在本地渲染，无需AI视频生成器。适合希望用Claude Code自动化制作动画短片的创作者。
- mylea1/phongentKotlin · 176 Stars
多设备协同控制、任务分配、消息集中查看
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作者描述
基于 Mika 的 iOS / Android 多设备 agent 主控与安卓执行端
编报时的 AI 中文解读
phongent 是一个多设备 agent 协同控制项目，允许用户通过 iPhone 或安卓手机连接多台安卓设备，向全部、分组或指定设备下发任务，并集中查看执行结果、消息和实时画面。适用于需要同时管理多台安卓设备并自动化执行任务的用户。
- zane-tv/tiktok-live-temple-rpcJavaScript · 170 Stars
直播互动、AI语音合成、虚拟仪式
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作者描述
Chùa Linh Ứng Online — TikTok Live RPC 9:16 Interactive Buddhist Temple (Bun.js + ZeroTTS)
编报时的 AI 中文解读
构建一个9:16竖屏的在线佛教寺庙直播系统，支持TikTok Live互动，观众通过评论、点赞、送礼等触发烧香、祈福、求签等仪式，并集成越南语AI语音朗读。
- kentjuno/chanh-dien-onlineHTML · 139 Stars
直播互动、虚拟佛堂、语音朗读
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作者描述
Chánh điện online 2.5D + bộ overlay TikTok LIVE (Node, Edge TTS). MIT.
编报时的 AI 中文解读
这是一个用于TikTok LIVE的2.5D在线佛堂项目，观众通过评论进入虚拟佛堂，赠送礼物可触发回向朗读，并包含禅乐、钟声等音效。适合希望为直播增添互动宗教氛围的主播。
- jmars125/xcx-recompC · 119 Stars
游戏重编译
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作者描述
Static recompilation of Xenoblade Chronicles X : Definitive Edition to native Windows x86-64, with a Vulkan renderer. Game files not included.
编报时的 AI 中文解读
将《异度神剑X：决定版》静态重编译为原生Windows x86-64应用，使用Vulkan渲染器，不包含游戏文件，需用户自备合法游戏文件。
- sqlpxc/airhandRust · 102 Stars
远程桌面、多屏监控、音频传输
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作者描述
High-performance remote desktop over QUIC · Rust + Tauri + React
编报时的 AI 中文解读
Airhand 是一个高性能远程桌面程序，基于 QUIC 协议，支持 Windows 和 Linux（X11）系统。它既是主机端也是控制端，可同时控制多台电脑，支持硬件编码、低延迟传输、音频流、剪贴板同步等功能。适用于需要低延迟、低带宽远程控制的用户。
- Aevonix/FlashAlignPython · 101 Stars
模型对齐切换、消息通道管理、工具集成
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作者描述
ReAlign models instantly, on demand. Per-request alignment for verified users and channels, or Always On. Use directly or with Hermes, OpenClaw and custom harnesses.
编报时的 AI 中文解读
FlashAlign 是一个用于按请求实时对齐大语言模型的工具，支持对已验证用户和频道应用消融（abliteration）等对齐配置文件，或设为始终开启（Always On）模式。适合需要在推理时动态调整模型行为（如减少拒绝）的开发者和研究者，可直接运行或与 Hermes、OpenClaw 等框架集成。
其余 12 个项目见收录列表。