#Coding Agent Workflow Toolkit Meta Github

AI Agents in Github Co-Pilot 🚀 Github released Agentic Mode in CoPilot and people with VsCode insider can use it now #coding #vscode #developer #tech

Most people are running one AI agent… while others are running entire teams. RuFlow turns Claude Code into a 60+ agent system that researches, codes, tests, and improves together. Manager agents → coordinate Worker agents → execute Shared memory → gets better over time And the smartest part: It routes tasks automatically simple work to cheaper models, complex work to powerful ones. That means lower cost + higher output. Reality check: This won’t magically fix bad inputs. If your instructions suck, your results will too. But if you know how to use it, this is serious leverage. Comment “flow” or DM “flow” and I’ll send you the full setup guide. #aitools #claudecode #automation #aiagents #productivity

Coding a app with react native #code #programmer

Comment "19" and follow me to get the 19 agent skills repo. A Google engineer open sourced the cheat code for AI coding agents. Addy Osmani released agent-skills, 19 production-grade engineering workflows turning your AI agent into a senior developer. Spec-driven development, incremental implementation, test-driven development, code reviews, security hardening, CI/CD. Without these, your agent skips the spec, skips the tests, and ships broken code. Agents take the shortest path by default. These skills enforce every single step. How do you make AI agents write better code? What are AI agent skills? How do you stop AI coding agents from shipping broken code? Free and open source on GitHub. #coding #programming #ai #aitools #technology

Comment “GITHUB” to get the links! 🔥 Trying to build software without understanding Git and GitHub is like coding without saving your work. If you want real collaboration skills, clean version control, and production-ready workflow confidence, this mini roadmap is your launchpad. ⚡ Git Explained in 100 Seconds The fastest way to grasp commits, branches, merges, and why version control is the backbone of every engineering team. 📚 Git Tutorial for Beginners: Learn Git in 1 Hour A practical, no-nonsense walkthrough of Git basics, commit history, branching, merging, resolving conflicts, and the workflows developers actually use. 🎓 How To Use GitHub for Beginners Your full intro to GitHub: repos, pull requests, issues, collaboration patterns, and how modern teams ship code together. 💡 With these Git + GitHub resources you will: 🚀 Work like a real engineer, not like “someone who uploads code sometimes” 🧠 Understand branching strategies, PR reviews, and team workflows 🏗 Bridge the gap between writing code and maintaining professional projects ☁ Level up for Backend, Cloud, DevOps, Open Source, and Production Engineering If you want to move from “I can code” to “I can ship software with a team,” GitHub isn’t optional, it’s foundational. 📌 Save this post so you never lose this GitHub roadmap. 💬 Comment “GITHUB” and I’ll send you all the links! 👉 Follow for more Backend Engineering, System Design, and Career Growth.

There are 10,000+ Claude Code plugins, but you only need 6: Plugins are add-ons that extend what Claude Code can do. 🔹 Superpower – Plans before coding (90K+ GitHub stars) 🔹 Frontend Design – Kills generic AI purple slop (by Anthropic) 🔹 Code Review – 5 agents reviewing in parallel 🔹 Security Guidance – Finds vulnerabilities before users do 🔹 Claude Mem – Remembers context across sessions 🔹 Gstack – Built by YC’s CEO, 6 skills in one Comment “PLUGINS” and I’ll send the full list.

GitHub to master ML 😎 This repo will teach you the basics of Python for machine learning and data science, starting from the basics. What’s nice about this repo is that it also has you work through some simple real-world examples to solidify your understanding of concepts! There’s also a link to a more in depth 10 hour YouTube video. Follow for more free coding resources ✅ #code #coding #tech #datascience #learntocode

Comment "GSTACK" and I'll send you the link to set it up The CEO of Y Combinator just open-sourced his entire AI setup on GitHub. It's called gstack. 23 tools that turn Claude Code into a full team. CEO, designer, engineering manager, release manager, QA. All built in. This is the exact system Garry Tan uses every day to run the biggest startup accelerator in the world. One-command install. 64,000+ stars on GitHub. Completely free. #ai #aitools #claude #claudecode #ycombinator #garrytan #gstack #freeai #aiproductivity

Decode Any GitHub Project 🧠 Comment “CODE” and we’ll DM you the tool to uncover prompts behind real projects. [GitHub Projects, AI Prompts, Dev Tools] #github #ai #codingtools #developers #aihacks

Combining Claude Code with NotebookLM automates content creation. Install NotebookLM.py repository to execute tasks from Claude Code. Build a research agent modeled on yourself or your company to research and create unlimited content. Comment “lm” for repository link and quickstart guide. #claudecode #notebooklm #aiautomation #contentcreation #aihacks Keywords: Claude Code, NotebookLM, AI automation, content creation, research agent, AI tools, productivity hacks, Google AI, repository setup, content strategy, workflow automation, AI integration

Comment "PROMPTS" to get this Github Repo with AI System Prompts from Top Companies. A massive leak just hit. It exposed full system prompts from top AI coding tools. Think Cursor. Manus. Bolt. Lovable. And more. From startups to big players like Devin AI. Replit. Perplexity. The GitHub repo has it all, check Augment Code, Claude Code, Cluely, CodeBuddy, Comet, Cursor, Devin AI, Junie, Kiro, Leap.new, Lovable, Manus, Notion AI, Orchids.app, Perplexity, Poke, Qoder, Replit, Same.dev, Trae, Traycer AI, VSCode Agent, Warp.dev, Windsurf, Xcode, Z.ai Code, Dia, v0, even open-source ones, internal tools too, AI models, everything. Why does this matter to you? As an AI builder. It's a treasure chest. Real prompts from tools making millions. Study them. See the patterns. Pros use these to make AI sharp at coding. Debugging. App-building. Take Cursor's prompts. They handle multi-file edits. Context-aware refactoring. Copy these. Use in your own Cursor work. Or custom agents. Manus and Lovable? They chain steps for no-code apps. Fits your Make.com setups. n8n automations. Devin AI and Replit show task breakdown. Great for your startup prototypes. Plus extras. Warp.dev tools. v0. VSCode Agent. Edges in UI generation. Terminal AI. Look close. Role definitions. Few-shot examples. Error loops. Output formats. Battle-tested stuff. I tried this myself last week. Asked Claude to tweak a Cursor prompt. Built a quick app agent. Worked like a charm. Like handing your brain a map. You're a software engineer. Deep in no-code AI apps. This fits perfect. Paste into Claude. Cursor. GitHub Copilot. Adjust for free tools. Google's Gemini. Open-source Llama. Build stronger agents. Launch MVPs quick. Pro tip. Fork the repo. Test with Ollama local. Your next tool? Could be it. #systemprompts #cursorai #lovableai #Perplexity #githubrepo

(4 free plugins) ⬇️ claude-mem (persistent memory) Gives Claude Code persistent memory so it doesn’t need your whole history or files every session; used well on ongoing projects, it can realistically cut “rehashing context” input tokens by around 80–90% for you. The Context Manager plugin Does rolling conversation compression (summarizing older turns, keeping recent ones verbatim), which typically trims long coding chats by roughly 30–50% tokens while still feeling continuous. Claude Context (semantic code search) Lets Claude pull only the specific functions or snippets it needs instead of whole files, so per‑request code tokens usually drop on the order of 40–70% once your repo is indexed. Superpowers‑style plugins Turn your long, reusable prompts (SEO systems, refactor recipes, content frameworks) into short commands or tasks, which in everyday use often cuts 15–40% of tokens from each repeated workflow. Comment “hack” I will send you the links to all the plugins. (Switch to Codex) Speaking from my own experience, I recently ran an end-to-end lead automation inside codex sing only natural language prompting—it was very intuitive and easy to navigate. It continued running for over 5 hours without hitting any rate limits. Codex also uses a different limiting model: instead of a small fixed token bucket, your main constraint is the “reasoning time” within that 5-hour window. Across multiple benchmarks, Claude tends to use roughly 2–4× more tokens than Codex on identical coding tasks. This is largely because Claude “thinks out loud,” explains its reasoning, and often spins up more sub-agents. So next time, instead of waiting for your tokens to reset, give @openai Codex a try! #claude #aihacks #openai #automation #claudecode