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Contents

GitHub
AI Infra·2025
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Anthropic Sandbox Runtime (srt)

Anthropic (anthropic-experimental)·Anthropic

Enforces filesystem and network limits on arbitrary processes at the OS level, no container required. Uses macOS Seatbelt, Linux bubblewrap, and the Windows Filtering Platform; built to sandbox MCP servers and AI agents under a secure-by-default model.

#anthropic#claude-code#mcp-server#nodejs#typescript+3
GitHub
AI Agent·2025
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Claude Skills

jeffallan (Jeff Smolinski)·Jeff Smolinski

Bundles 66 context-activated skills for Claude Code spanning backend, frontend, DevOps, security, and data/ML, loading only the relevant reference per request. A 'Common Ground' step surfaces hidden project assumptions before coding starts.

#claude#claude-code#agent-skills#plugin#ai-coding+1
GitHub
AI Image·2025
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Chandra OCR

Datalab (datalab.to), Vik Paruchuri·Datalab

Converts images and PDFs into structured Markdown, HTML, or JSON while preserving layout, handling tables, math, handwriting, charts, and chemistry diagrams across 90+ languages. Runs locally via HuggingFace or against a vLLM server.

#ocr#vllm#huggingface#pytorch#python+3
GitHub
AI Coding·2025
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Superset (superset-sh)

superset-sh, Avi (avimakesrobots) +2·Superset

Desktop app that runs many CLI coding agents — Claude Code, Codex, Cursor, Gemini — in parallel, each in its own git worktree and branch. A built-in diff viewer, terminal, and PR tracking let you dispatch and review 10+ agents at once.

#ai-coding#ai-agent#claude-code#codex#copilot+6
GitHub
AI Agent·2025
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AI-Traderv2 (AI-Trader)

HKUDS·Data Intelligence Lab, The University of Hong Kong

Lets AI agents (Claude Code, Codex, Cursor, and others) register through a guide and join a shared paper-trading arena, where they publish signals, debate ideas, and copy-trade each other across stocks, crypto, and Polymarket markets.

#finance#agent-skills#ai-agent#github#ai-api
GitHub
AI Coding·2025
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Letta Code

Letta AI

A stateful agent harness, shipped as a CLI, whose agents keep memory, skills, and prompts across sessions instead of resetting each run. Context is git-versioned via MemFS, and agents can rewrite their own prompts and skills over time.

#agent-skills#ai-coding#llm#ai-api#docker+2
GitHub
Embodied AI·2025
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ESPectre

Francesco Pace

Detects motion from Wi‑Fi channel state information (CSI) on cheap ESP32 boards and integrates natively with Home Assistant; offers an optional on‑device ML detector that requires no calibration.

#github#ai#ai-inference#ai-deploy#privacy+1
GitHub
AI Agent·2025
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OpenSkills

Numman Ali

Installs Claude Code-format skills into agents without native support — Cursor, Windsurf, Aider, Codex — by writing the same <available_skills> XML into their AGENTS.md. Skills stay plain files, so no MCP server is needed.

#agent-skills#ai-tools#github#anthropic
Hugging Face
AI Dataset·2025
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lightonai/embeddings-fine-tuning

lightonai

Provides mined hard negatives and relevance scores for 1.88M queries across seven retrieval datasets, enabling contrastive fine-tuning and nv-retrieve filtering; includes full 2048 mined negatives per query, paired query/document splits, and parquet-formatted files for large-scale training.

#embeddings#huggingface#nlp#RAG#ai-train+1
GitHub
AI Agent·2025
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awesome-agent-skills

VoltAgent

Curated index of 1,100+ official and community Agent Skills for extending AI agents across platforms — Claude Code, Codex, Gemini CLI, Cursor, GitHub Copilot, OpenCode, and more. Focuses on hand-picked, engineering-authored skills, organized by vendor, paths, and quality guidance.

#agent-skills#claude-code#codex#gemini-cli#cursor+5
GitHub
AI Client·2025
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SEO Machine

TheCraigHewitt, Anthropic·Castos

Turns content briefs into SEO-optimized long-form articles via chained Claude Code commands and specialized subagents. Pulls live GA4, Search Console, and DataForSEO data to ground keyword research, drafting, and on-page optimization in real rankings.

#claude-code#anthropic#AIGC#ai-tools#blog+5
GitHub
AI Agent·2025
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Fara-7B

Ahmed Awadallah, Yash Lara +10·Microsoft Research, Microsoft

Automates multi-step web tasks by perceiving webpages as pixels and issuing low-level mouse, keyboard and scroll actions. A 7B-parameter multimodal agent trained on 145K synthetic trajectories (FaraGen), designed for on-device deployment and efficient task completion (~16 steps/task).

#agent-skills#multimodal#llm#vision#microsoft+7
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