The attention layer for LLM agents — see what the model fires before it ships.
GitHub repository with 5 stars and 0 forks.
Language: Python
Topics: prompt-engineering, mcp, ai-safety, llm, llm-evaluation, agent, claude-code, cursor
Trending score 0.03, activity score 0.02, stars gained +0, forks gained +0.
2026-06-05: 5 stars and 0 forks.
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95% fewer tokens, same answers. Library, proxy, MCP server.
GitHub repository with 13,768 stars and 870 forks.
Trending score: 5.69; stars gained: +2,829; forks gained: +175.
Language: Python
Topics: agent, ai, anthropic, compression, context-engineering, context-window
Academic Research Skills for Claude Code: research → write → review → revise → finalize
GitHub repository with 27,484 stars and 2,256 forks.
Trending score: 5.52; stars gained: +1,079; forks gained: +89.
Language: Python
Topics: academic-pipeline, academic-writing, ai-research, claude, claude-code, literature-review
A tremendous feat of documentation, this guide covers Claude Code from beginner to power user, with production-ready templates for Claude Code features, guides on agentic workflows, and a lot of great learning materials, including quizzes and a handy "cheatsheet". Whether it's the "ultimate" guide to Claude Code will be up to the reader :)
GitHub repository with 4,700 stars and 633 forks.
Trending score: 3.24; stars gained: +95; forks gained: +16.
Language: Python
Topics: agentic-coding, ai-assistant, ai-coding, ai-pair-programming, anthropic, best-practices
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
GitHub repository with 26,312 stars and 5,812 forks.
Trending score: 3.17; stars gained: +43; forks gained: +7.
Language: Python
Topics: agentops, agents, ai, ai-governance, apache-spark, evaluation
AI Observability & Evaluation
GitHub repository with 9,989 stars and 909 forks.
Trending score: 3.03; stars gained: +17; forks gained: +2.
Language: Python
Topics: llmops, ai-monitoring, ai-observability, llm-eval, aiengineering, datasets
Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.
GitHub repository with 19,434 stars and 1,496 forks.
Trending score: 2.37; stars gained: +10; forks gained: +1.
Language: Python
Topics: evaluation, hacktoberfest, hacktoberfest2025, langchain, llama-index, llm
The agent that grows with you
GitHub repository with 181,889 stars and 31,208 forks.
Trending score: 5.95; stars gained: +1,867; forks gained: +361.
Language: Python
Topics: ai, ai-agent, ai-agents, anthropic, chatgpt, claude
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95% fewer tokens, same answers. Library, proxy, MCP server.
GitHub repository with 13,768 stars and 870 forks.
Trending score: 5.69; stars gained: +2,829; forks gained: +175.
Language: Python
Topics: agent, ai, anthropic, compression, context-engineering, context-window
Academic Research Skills for Claude Code: research → write → review → revise → finalize
GitHub repository with 27,484 stars and 2,256 forks.
Trending score: 5.52; stars gained: +1,079; forks gained: +89.
Language: Python
Topics: academic-pipeline, academic-writing, ai-research, claude, claude-code, literature-review
Learn it. Build it. Ship it for others.
GitHub repository with 28,622 stars and 4,680 forks.
Trending score: 5.32; stars gained: +1,261; forks gained: +238.
Language: Python
Topics: agents, ai, ai-agents, ai-engineering, computer-vision, course
GitHub repository with 30,029 stars and 4,231 forks.
Trending score: 4.88; stars gained: +688; forks gained: +114.
Language: Python
An opinionated list of Python frameworks, libraries, tools, and resources
GitHub repository with 301,396 stars and 28,042 forks.
Trending score: 4.60; stars gained: +518; forks gained: +24.
Language: Python
Topics: awesome, python, collections, python-frameworks, python-libraries, python-tools
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95% fewer tokens, same answers. Library, proxy, MCP server.
GitHub repository with 13,768 stars and 870 forks.
Trending score: 5.69; stars gained: +2,829; forks gained: +175.
Language: Python
Topics: agent, ai, anthropic, compression, context-engineering, context-window
Academic Research Skills for Claude Code: research → write → review → revise → finalize
GitHub repository with 27,484 stars and 2,256 forks.
Trending score: 5.52; stars gained: +1,079; forks gained: +89.
Language: Python
Topics: academic-pipeline, academic-writing, ai-research, claude, claude-code, literature-review
A tremendous feat of documentation, this guide covers Claude Code from beginner to power user, with production-ready templates for Claude Code features, guides on agentic workflows, and a lot of great learning materials, including quizzes and a handy "cheatsheet". Whether it's the "ultimate" guide to Claude Code will be up to the reader :)
GitHub repository with 4,700 stars and 633 forks.
Trending score: 3.24; stars gained: +95; forks gained: +16.
Language: Python
Topics: agentic-coding, ai-assistant, ai-coding, ai-pair-programming, anthropic, best-practices
Extracted system prompts from Anthropic - Claude Code, Claude Design, Opus 4.8, Sonnet 4.6. OpenAI - ChatGPT 5.5 Thinking, GPT 5.5 Instant, Codex, Google - Gemini - 3.5 Flash, 3.1 Pro, Antigravity, xAI - Grok, Cursor, Copilot, VS Code, Perplexity, and more. Updated regularly.
GitHub repository with 41,275 stars and 6,843 forks.
Trending score: 3.20; stars gained: +54; forks gained: +13.
Language: JavaScript
Topics: ai, anthropic, awesome, chatbot, chatgpt, claude
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
GitHub repository with 26,312 stars and 5,812 forks.
Trending score: 3.17; stars gained: +43; forks gained: +7.
Language: Python
Topics: agentops, agents, ai, ai-governance, apache-spark, evaluation
What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?
GitHub repository with 22,915 stars and 1,748 forks.
Trending score: 3.09; stars gained: +36; forks gained: +3.
Language: TypeScript
Topics: agents, ai, context-window, framework, llms, memory