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GitHub热门项目 | 754 structured cybersecurity skills for AI agents · Mapped to 5 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND & NIST AI RMF · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 26 security domains · Apache 2.0 | Stars: 10,997 | 886 stars today | 语言: Python
GitHub热门项目 | Kronos: A Foundation Model for the Language of Financial Markets | Stars: 26,898 | 401 stars today | 语言: Python
GitHub热门项目 | Fully automatic censorship removal for language models | Stars: 22,036 | 211 stars today | 语言: Python
GitHub热门项目 | Taste-Skill - gives your AI good taste. stops the AI from generating boring, generic slop | Stars: 24,364 | 2,715 stars today | 语言: Shell
GitHub热门项目 | Open source repository of plugins primarily intended for knowledge workers to use in Claude Cowork | Stars: 17,306 | 695 stars today | 语言: Python
GitHub热门项目 | The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. | Stars: 196,090 | 2,062 stars today | 语言: JavaScript
GitHub热门项目 | A skill file for removing AI tells from prose | Stars: 5,745 | 664 stars today | 语言:
GitHub热门项目 | Graphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more. | Stars: 39,985 | 4,465 stars today | 语言: TypeScript
GitHub热门项目 | 利用AI大模型，一键生成高清短视频 Generate short videos with one click using AI LLM. | Stars: 62,262 | 1,742 stars today | 语言: Python
I used to live in VS Code with GitLens pinned — the branch graph, heat-mapped blame, the lens annotations. That was my git workflow. Then 2026 happened. With Cursor, Claude Code, and Codex doing the actual editing, the editor itself became optional. The only thing dragging me back was GitLens. That felt wasteful — booting an entire IDE just to peek at commit history. The agent runs the git commands now; I only need to sanity-check the result, occasionally, when something looks off. So I built gitwink — the smallest possible tool for that loop. A tray icon that expands into a glance, hands the commit off as AI context, and gets out of the way. Read-only by design. It cannot commit, push, merge, or modify anything. If I need git surgery, I tell the agent. The 0.5-second confirm loop agent commits → tray click → inline expand → "Copy as AI context" → paste into Claude/Codex/Cursor → "did the agent do this right?" No window switching. No IDE boot. The whole loop fits inside a glance. What's in it Tray-resident (Windows tray / macOS menu bar) — click to toggle, global hotkey Ctrl+Shift+G to summon from anywhere. Right-click the tray icon for Reset position / Open settings file / Quit. First-run discovery that walks your usual code dirs ( source , Documents , Projects , Code , Dev , repos , Desktop , every non-system drive on Windows; ~/Projects , ~/Code , ~/Developer on macOS) and caches the result in SQLite. No "add repo" friction. Unified commit timeline across all repos, with chips above for filtering by Repo (search + pinning), Time range (24h / 3d / 7d / 30d / All), and Authors (multi-select with counts). Per-row markers — ● commit · ◆ merge · ★ tagged — and branch label badges when a commit isn't on the currently checked-out branch. Single-repo DAG view — pick a repo and the panel switches to a per-branch graph with a custom SVG lane drawer (eight-colour palette, hashed from branch name; main / master / develop kept neutral). Inline expand on click — commit body +
What if a development board could be as friendly as an Arduino, yet powerful enough to drive industrial-grade robots? That is exactly the gap the new G2 Nano sets out to close. Most hobby boards handle simple robot builds with ease, but they hit a wall once a project demands tight, simultaneous control of several motors. Embedded systems engineer Ryan Strace noticed that the custom controllers built for these complex machines tend to look remarkably alike, with motor coordination as the recurring headache. Rather than reinventing that hardware on every project, he designed a single accessible platform to handle it, and the G2 Nano is the result. Precise motor control usually leans on closed-loop techniques like PID, but real-world gremlins such as integrator windup, sensor noise, mechanical saturation, and phase delay can all degrade performance. Robots also need smooth multi-axis motion with managed acceleration to avoid jerky, stressful movement, plus solid fault handling so an unexpected state does not wreck expensive parts. Strace is tackling all of this with a low-cost motion-control IC he is developing, and the G2 Nano is the high-performance platform built to prove out that future chip. What's under the hood Processor: NXP Arm Cortex-M7 clocked at a brisk 1 GHz Wireless: u-blox MAYA-W1 module with dual-band Wi-Fi and Bluetooth Motion sensing: six-axis IMU (3-axis accelerometer plus 3-axis gyroscope) and a dedicated magnetometer for compass heading Form factor: just 0.8 by 3 inches, breadboard-friendly, on a six-layer PCB stackup for clean high-speed signals On the software side, the board targets native micro-ROS and the Zephyr real-time operating system, with planned MicroPython support so you can prototype in Python without paying the usual speed penalty, thanks to that unusually high clock. Every design file and document is open-source and published on GitHub. Build it yourself If you want to follow along, the core ingredients are clear: an NXP Cortex-M7 a
This is a submission for the GitHub Finish-Up-A-Thon Challenge What I...
The Trust Identity Protocol is a free, open, post-quantum, patented standard for verified human identity and AI content provenance on the public internet. Built by The AI Lab Intelligence Unobscured, Inc.
Two stories landed in the same news cycle. Microsoft cancelled most internal Claude Code licenses....