#javascript #ai #anthropic #chatbots #chatgpt #claude #gemini #generative_ai #google_deepmind #large_language_models #llm #openai #prompt_engineering #prompt_injection #prompts

There is a collection of system prompts used by popular chatbots like ChatGPT and others. These prompts are instructions that guide how chatbots respond. They are now available publicly on GitHub, which can be very helpful for users. By seeing these prompts, users can understand how chatbots work and even learn how to create their own AI tools. This can help developers build better AI applications and improve their understanding of AI technology.

https://github.com/asgeirtj/system_prompts_leaks

#jupyter_notebook #chatgpt #finance #fingpt #fintech #large_language_models #machine_learning #nlp #prompt_engineering #pytorch #reinforcement_learning #robo_advisor #sentiment_analysis #technical_analysis

FinGPT is an open-source AI tool designed specifically for finance, helping you analyze financial news, predict stock prices, and get personalized investment advice quickly and affordably. Unlike costly models like BloombergGPT, FinGPT can be updated frequently with new data at a low cost, making it more accessible and timely. It uses advanced techniques like reinforcement learning from human feedback to tailor advice to your preferences, such as risk tolerance. You can use FinGPT for tasks like sentiment analysis, robo-advising, fraud detection, and portfolio optimization, helping you make smarter financial decisions with up-to-date insights.

https://github.com/AI4Finance-Foundation/FinGPT

#javascript #ai #github_copilot #prompt_engineering

You can improve your GitHub Copilot experience by using the Awesome GitHub Copilot Customizations, a collection of ready-made prompts, instructions, and chat modes tailored for different coding tasks and roles. This toolkit helps you write better code faster by providing focused code suggestions, enforcing coding standards, and offering expert AI personas for specialized help. You can easily add these customizations to editors like VS Code using the MCP Server. This saves you time, boosts productivity, ensures consistent code quality, and helps you learn best practices while coding. It also supports collaboration and onboarding by standardizing workflows and documentation.

https://github.com/github/awesome-copilot

#jupyter_notebook #aiagent #chatgpt #finance #fingpt #large_language_models #multimodal_deep_learning #prompt_engineering #robo_advisor

FinRobot is a free open-source platform using AI agents and large language models for easy financial analysis. It automates stock predictions, equity reports from 10-K filings, risk checks, valuations like P/E ratios, and trading strategies with real-time data from news and markets. Install via Python, add API keys, and run demos for instant insights. This saves you hours on complex research, delivers pro-level reports and forecasts accurately, and helps make smarter investment decisions without expert skills.

https://github.com/AI4Finance-Foundation/FinRobot

#python #agentic_ai #agentic_coding #ai_coding_agent #ai_plugins #anthropic_claude #claude_ai #claude_ai_skills #claude_code #claude_code_plugins #claude_code_skills #claude_skills #claudecode_subagents #developer_tools #devtools #mcp_tools #openai_codex #prompt_engineering

Claude Code Skills offers 169 free, ready-to-use plugins that turn AI coding agents like Claude Code, OpenAI Codex, and OpenClaw into experts in engineering, marketing, product, compliance, and more. Install easily via simple commands to add skills like security auditing, test automation, or C-level advice, with 160+ Python tools included. This saves you time by automating complex tasks, boosting code quality, and handling grunt work so you focus on creative problem-solving and faster results.

https://github.com/alirezarezvani/claude-skills

#typescript #analytics #autogen #evaluation #langchain #large_language_models #llama_index #llm #llm_evaluation #llm_observability #llmops #monitoring #observability #open_source #openai #playground #prompt_engineering #prompt_management #self_hosted #ycombinator

Langfuse is a free, open-source platform to build, monitor, evaluate, and debug AI apps using large language models (LLMs). It offers tracing for app logic, prompt management, evaluations, datasets, a playground, and easy integrations like OpenAI, LangChain, and LlamaIndex. Deploy it on Langfuse Cloud (free tier) or self-host with Docker in minutes. This helps you quickly spot issues, improve prompts without slowing apps, test reliably, and speed up development—saving time and boosting AI performance.

https://github.com/langfuse/langfuse

#python #academic_pipeline #academic_writing #ai_research #claude #claude_code #literature_review #peer_review #prompt_engineering

# Academic Research Skills for Claude Code

This is a comprehensive toolkit that helps you write research papers from start to finish. Instead of AI writing your paper alone, it works as your research partner—handling the tedious work like finding sources, checking citations, and organizing arguments, while you focus on the thinking and writing that only you can do.

The system includes four main tools: Deep Research (for finding and organizing information), Academic Paper (for writing), Academic Paper Reviewer (for getting feedback), and Academic Pipeline (which coordinates everything together). You can use individual tools or run the complete pipeline. It supports multiple languages, citation formats, and paper types. The toolkit emphasizes human control at every step—you make the final decisions, and the AI flags potential problems like hallucinated references or weak arguments. Installation takes 30 seconds via plugin marketplace, and it costs roughly $4–6 to write a complete 15,000-word paper.

https://github.com/Imbad0202/academic-research-skills

#python #agent #ai #anthropic #claude_code #compression #context_engineering #context_window #cursor #fastapi #langchain #llm #mcp #openai #prompt_engineering #proxy #python #rag #token_optimization #tokens #typescript

Headroom is a local tool for AI agents that shrinks prompts, logs, files, and chat history before sending them to an LLM, often cutting tokens by 60–95% while keeping the same answer quality. It can work as a library, proxy, MCP server, or agent wrapper, so you can save tokens, speed up workflows, and still recover the original content when needed.

https://github.com/chopratejas/headroom

#javascript #ai #anthropic #caveman #claude #claude_code #llm #meme #prompt_engineering #skill #tokens

This tool helps agents answer in caveman style: fewer words, same technical meaning, and often much lower token cost. You can choose levels like lite, full, ultra, or wenyan, and it also includes commands for shorter commit messages, quick PR reviews, stats, and compressing memory files; the benefit is faster replies, lower cost, and longer context for your work.

https://github.com/JuliusBrussee/caveman

#python #cfg #generative_ai #json #llms #prompt_engineering #regex #structured_generation #symbolic_ai

Outlines is a Python library that guarantees large language models produce structured outputs (like JSON, XML, or custom schemas) directly during generation, not after. By simply specifying your desired output type using Python syntax (e.g., `int` or a Pydantic model), it mathematically ensures the result matches your structure exactly. This benefits you by eliminating broken JSON, parsing errors, and fragile regex code, making your AI applications reliable, predictable, and ready for production use without post-generation fixes.

https://github.com/dottxt-ai/outlines