K-Dense-AI / scientific-agent-skills
A collection of 177 validated scientific skills for AI agents, covering biology, chemistry, medicine, and data analysis, plus 100+ scientific database references.
K-Dense-AI / scientific-agent-skills
chrislgarry / Apollo-11
Original Apollo 11 Guidance Computer source code for the Command Module (Comanche 055) and Lunar Module (Luminary 099).
anthropics / financial-services
Reference Claude agents, skills, and data connectors for investment banking, equity research, private equity, and wealth management workflows.
mnfst / awesome-free-llm-apis
A curated list of LLM APIs that offer permanent free tiers for text inference, with base URLs, models, and rate limits.
ConardLi / garden-skills
A collection of Agent Skills for Claude Code, Cursor, Codex and other AI coding agents covering web design, retrieval, image prompting and video.
byoungd / up
An open, bilingual Chinese-language book-guide on lifelong learning in the AI era, covering English study, AI learning, real projects, and personal recovery.
shanraisshan / claude-code-best-practice
A curated reference of Claude Code best practices covering subagents, commands, skills, hooks, memory, and workflows.
alirezadir / AIMLInterviews
A study guide and interview-prep curriculum for AI/ML technical roles at big tech, covering coding, ML breadth, system design, and behavioral rounds.
edoardottt / awesome-hacker-search-engines
A curated Markdown list of search engines for security work, covering servers, vulnerabilities, exploits, leaks, and threat intelligence.
OWASP / wstg
A community-written guide covering methods and test cases for security testing web applications and web services.
xbtlin / ai-berkshire
A set of Claude Code and Codex skills that run value-investing company research using four investors' methodologies via multi-agent analysis.
hefengxian / my-ielts
A Vue-based static site collecting IELTS prep materials covering vocabulary, grammar, listening, reading, and writing.
exacity / deeplearningbook-chinese
Chinese translation of the Deep Learning textbook by Goodfellow, Bengio, and Courville, with community proofreading.