Cursor

Cursor AI

Cursor AI

Cursor AI

Cursor AI

Cursor AI

Cursor AI

Cursor AI

Cursor AI

Cursor AI

Cursor AI

naksha-studio v5 is out. It now remembers your project so you stop explaining your stack every session.

Been building naksha-studio for a while now. It's a plugin that gives you a virtual design agency as slash commands inside Claude Code, Cursor, Windsurf, and Gemini CLI. 62 commands, 26 specialist roles, all the design work you'd normally bounce between tools to do. The problem was every session started from zero. New chat, explain your stack again. Brand color, framework, grid system, WCAG level. Every time. v5 fixes that with project memory. What's new: /naksha-browse captures a live site through Playwright and stores the findings. Layout grid, type scale, color palette, UX patterns, all written to your project memory. Run it on your competitors or sites you admire and every future design command uses those as reference automatically. /naksha-remember persists design constraints. "Grid is 8px. No dark mode. WCAG AA required." Classified and stored. Never repeated again. Both write to .naksha/project.json and 5 existing commands (/design, /brand-kit, /design-system, /design-score, /accessibility-audit) read it automatically from that point on. The Stop hook also processes memory blocks written during a session so context you establish mid-conversation survives to the next one. GitHub: https://github.com/Adityaraj0421/naksha-studio If you were already using it, just git pull. No reinstall needed. Run /naksha-init to upgrade your existing project to the v5 schema. Feedback welcome, especially on whether the memory actually reduces your setup friction. submitted by /u/Known-Delay-9689 [link] [comments]

5 Stars! Websites to Native Mobile App Plugin/Skills!

Small update: WebToMobile just hit 5 stars on GitHub 🎉 I know that’s tiny in internet numbers, but it means a lot because this started as a very specific problem: “Can we give AI coding agents a better workflow for turning websites into mobile apps?” Instead of asking Claude/Cursor/Codex to “make this website an app” and hoping for the best, WebToMobile gives the agent a structured path: - audit the website or repo - separate URL-only UI/UX work from real source-code migration - map web routes to mobile screens - identify reusable vs rewrite-required code - flag mobile-native gaps like auth, storage, cookies, OAuth, uploads, etc. - create a Markdown migration plan - wait for approval before writing code - build with Expo React Native - run QA/review checks The repo now includes commands for: - `/web-to-mobile` - `/mobile-resume` - `/mobile-scan` - `/mobile-review` - `/mobile-audit` - `/mobile-qa` It works best with a GitHub repo or local project, but live URLs can still be used for UI/UX planning. Repo: https://github.com/suntay44/web-to-mobile-magic-plugin Thanks to everyone who starred it or gave feedback. Next focus is making the install/update flow cleaner and improving framework coverage. submitted by /u/suntay44 [link] [comments]

I built an open-source Desktop App that gives your AI persistent memory across all platforms (100% Local SQLite, Zero-Docker)

Hey everyone, A few weeks ago I shared the CLI version of my project, ArcRift, on Reddit. After listening to your feedback—specifically the requests to remove heavy Docker dependencies and make it easier to install—I have just released the v1.6.1 Desktop App. If you regularly use LLMs for coding or research, you know the frustration of "amnesia." Every time you open a new chat, you have to painstakingly copy and paste your project structure and previous context just to get the AI up to speed. ArcRift is a 100% offline, local-first RAG and memory layer. It bridges the gap between your AI web chats (like Claude and ChatGPT) and your local tools (like Cursor or Claude Code) using a unified local database. I wanted something lightweight that did not require pulling Docker containers or subscribing to third-party memory APIs. It now runs as a native Tauri desktop app in your system tray, powered completely by local Ollama instances and a local SQLite database. We just launched a live website that outlines the details and demonstrates the features in action: Website: https://arcrift.vercel.app/ Codebase: https://github.com/Eshaan-Nair/ArcRift How it works & Core Features: Seamless Integration: The Chrome extension silently intercepts your prompts, surgically retrieves exactly the sentences relevant to your question from your database, and injects them before the prompt is sent to the LLM. Hybrid Search Retrieval: Uses sqlite-vec (with nomic-embed-text locally) + FTS5 keyword prefix matching to instantly find your past context. Knowledge Graph Extraction: An offline task queue uses a local LLM to extract entity relationships from your chats, mapping out a graph of your projects over time. Direct Codebase Indexing: The new Desktop App allows ArcRift to scan and index your actual project files into the graph, bridging the gap between your chat memory and your actual code architecture. Total Privacy (PII Redaction): The extension aggressively scrubs JWTs, API keys, emails, and IPs before data is even saved to your local disk. The extension works natively with Claude.ai, ChatGPT, DeepSeek, Gemini, Grok, and Mistral. If you save a conversation in ChatGPT today, you can instantly recall that exact context in Claude tomorrow. ArcRift is completely open-source (MIT). You can download the new .exe installer directly from the GitHub releases page. If you find this useful for your daily workflow, PRs are very welcome, and a star on GitHub helps the project get discovered! submitted by /u/Better-Platypus-3420 [link] [comments]

Moving from Figma to Cursor for Prototyping — How Are Teams Handling This?

TL;DR: UX designer experimenting with designing directly in Cursor + Claude Code instead of Figma. It feels much faster, but I’m struggling to understand how this works in a team setting. How are people sharing prototypes, collaborating, and gathering feedback? I’ve been a UX designer for years and recently started prototyping directly in the app using Cursor and Claude Code. It feels like a huge shift compared to designing in Figma first. The challenge is that my work now mostly lives locally. I have the repo set up, but I can’t push the generated code, so sharing with PMs, designers, stakeholders, and developers isn’t as straightforward as sending a Figma link. For those working this way: How do you share your prototypes? Do you deploy temporary versions somewhere? Do you still use Figma? How do teams collaborate when the design exists primarily as code? Curious to hear how others are handling this. submitted by /u/ClearDurian5921 [link] [comments]

What I learned shipping production code with Claude Code (beyond 'build me a SaaS')

Most people drive Claude Code like a slot machine: "build me a SaaS that makes money," hit enter, hope. You get a demo that looks great and collapses the moment it meets real traffic — usually with zero security and no idea how its own database works. After a lot of sessions, the thing that changed my output wasn't a better prompt, it was treating Claude Code as something I drive, not something I delegate to blindly: Memory architecture. I keep instruction files (CLAUDE.md / .cursor/rules) so the agent shares my conventions across sessions instead of re-deciding the stack every time. This alone killed most of the "it rewrote half my app" chaos. Verification discipline. The agent proposes, I verify — types, tests, a Lighthouse check — before anything gets committed. Claude is great at generating; it's terrible at being trusted unsupervised. MCP servers to give it real context (DB schema, my own docs) instead of letting it hallucinate the shape of my data. Scoping the task small. "Add this one endpoint with these constraints" ships. "Build the platform" wanders. Where it got interesting: once Claude Code stopped fighting me, I used it to actually build and self-host a proper stack — Hetzner VPS + Ploi, MySQL + Prisma, MinIO for S3-style storage, the whole environment in one Docker Compose file. The agent can absolutely help you stand that up if you give it the architecture and verify each step. The lesson: vibe coding shouldn't mean shipping something that gets hacked day one. Claude Code is a sharp tool — it just needs a driver with a workflow that respects SEO, security, and scalability. Happy to go into the memory setup or the verification loop if anyone wants specifics. (I also wrote longer notes on my site, but the meat is above.) submitted by /u/Silly_Subject_5199 [link] [comments]

Open-source Website to Mobile coding-agent plugin/skills

I’ve been working on a plugin/skill set for Claude Code, Cursor, and Codex called WebToMobile. The idea is simple: if you have a website or web app and want to turn it into a mobile app, the agent should not just start generating random React Native screens. Instead, it follows a migration workflow: Audits your website, GitHub repo, or local project Maps web routes/pages to mobile screens Separates reusable code from rewrite-required code Flags mobile-native gaps like auth, storage, cookies, OAuth redirects, uploads, push, etc. Creates a Markdown migration plan/checklist Waits for your approval Builds in Expo React Native Runs QA/review checks before claiming anything is done Important distinction: - If you give it only a live URL, it can help with UI/UX and visual structure. - If you give it the repo/local code, it can do a much deeper migration plan and implementation. It includes commands like: /web-to-mobile /mobile-resume /mobile-scan /mobile-review /mobile-audit /mobile-qa I built it because “make this website into an app” is usually too vague for AI agents. They need a defined path, not just a better prompt. Repo: https://github.com/suntay44/web-to-mobile-magic-plugin Would love feedback from people building with Expo, React Native, Claude Code, Cursor, or Codex. submitted by /u/suntay44 [link] [comments]

Claude Code efficiency

Hey, everybody! I’m currently using Claude code to build my own app, I tell Claude AI what I want to do/implement into my app and he writes me a prompt which then I feed into Claude code. I’ve been doing this and have been writing my app in React Native, so far so good, I’ve implemented an API and use Supabase as a back-end. My current stack is Claude Code for, well, Coding and fixes within the code, Claude Ai to write and create the idea of the implementation, supabase for the back end and Cursor to locally host my app to see the version before deploying into my domain. What I want to ask is, am I using Claude code to its potential? I feel like I use him quite efficiently and savvy, but I still feel like I’m not using him to its proper potential or not getting a 100% out of all the uses it has. Does anyone have any tips, skills, agents or any advice along those lines that would help me improve my app building or general usage within Claude? submitted by /u/NickToons203 [link] [comments]

[Open Source] I built a full Git MCP server in Go that doesn't just wrap bash. It uses tree-sitter, handles real plumbing (write-tree), and runs 100% locally.

I was tired of watching LLM agents fail at basic Git operations. Standard integrations pass raw text, hang on pagers, or scream because they can't parse unstructured ⁠git diff⁠ outputs. git-courer is a full Model Context Protocol (MCP) server written in Go that treats Git properly. No bash spawning, no unstructured text to parse. Everything communicates via structured JSON. Here is an actual commit message it generated completely locally: fix: fix mcp server connection handling WHY The previous implementation lacked proper error handling for connection failures in the MCP server, leading to unhandled panics or silent failures when the local LLM backend was unreachable. WHAT * Added connection timeout logic to the local client calls. * Implemented retry mechanisms with exponential backoff for transient backend errors. The Architecture & Tool Pack Read Tools (status, diff, history, blame): Completely structured JSON and fully paginated. A single ⁠status⁠ call replaces over 5 standard Git commands for the agent. Write Tools (commit, merge, rebase, branch, stash, stage, sync...): Every single mutation auto-creates a backup before executing. If the LLM messes up, a ⁠RESTORE⁠ command brings you back exactly where you were. Safety Model: Destructive operations (hard resets, force pushes, branch deletions) require an explicit ⁠confirmed=true⁠ gate. The agent is forced to ask you first. ⁠dry_run=true⁠ is also available for peace of mind. The Semantic Annotator (Why it's different) Instead of just feeding raw code to the LLM, git-courer uses ⁠go-enry⁠ + ⁠go-tree-sitter⁠ to parse the AST and tag every hunk semantically before the LLM even sees it. It detects tags like ⁠NEW_FUNC⁠, ⁠MOD_SIG⁠, ⁠MOD_BODY⁠, ⁠DELETED⁠, and ⁠BREAKING_CHANGE⁠. The commit type (⁠feat⁠, ⁠fix⁠, ⁠refactor⁠) is determined deterministically from these AST tags rather than guessed by the model. The Commit Pipeline Atomic Commits: One staged area = one commit. It actively prevents the agent from creating giant, messy multi-feature commits. In-Memory Previews: The ⁠PREVIEW⁠ tool uses ⁠write-tree⁠ to snapshot the staging area into a ⁠job_id⁠. The working tree is never touched during the preview stage. ⁠APPLY⁠ then uses ⁠commit-tree⁠ + ⁠update-ref⁠ to seal the deal cleanly. Client & Backend Support 13 Clients Configured Automatically: Runs out of the box with ⁠git-courer mcp setup⁠ for Claude Code, Cursor, Windsurf, OpenCode, Cline, Roo Code, VS Code, Zed, Claude Desktop, Continue, and more. 100% Local-First: Works with any backend exposing an OpenAI-compatible ⁠/v1⁠ API (Ollama, LM Studio, llama.cpp). The project is fully open source. I’d love to hear your thoughts on the architecture, the plumbing pipeline, or any features you'd like to see added! Repo: github.com/Alejandro-M-P/git-courer submitted by /u/blakok14 [link] [comments]

Introducing Machinaos[Fully Opensource]: OS That converts LLM Tokens to Work.

claude On May 13 Anthropic Culled the Usage of "Claude -p" Command which instantly killed the heavily 25x subsidization usage of Claude . People were using Openclaw , Hermes Agent and others things through claude cli using the "-P" command , but now the usage will be charged as Claude SDK API credits from their Pro[100$] or MAX[200$] Budgets. Using claude through their SDK is ~25x more expensive and burns credits super Fast. Once i Tried to Generate a Simple PDF report from my emails and it burned ~10$ in the Calude SDK Credits. Also Claude Code usage is very generous and barely hits the Weekly Quotas. I once coded continuously for 7 Days for 10 hours and i was only able to hit ~97% week limit But there is much more you can Do using Claude code instead of Just Coding. You can Add Tools and Sub Agents, etc and Convert it to Cowork and Design too. BTW Claude Cowork and Claude Design are Supper Token Hoggers and Hits Quotas Fast. Once I was using Calude Design and told it generate around 10 Design Themes and it burned through weekly quota with a Hour usage. Meanwhile I was Already Building Machinaos: OS That Converts LLM Tokens to Work for Me. I connect my socials , emails , web tools, browser, etc and use it to generate websites, read emails and generate PDF Reports and mails them to others emails or to someone on my Socials like WA. So I Added a Claude Code Agent to the Machinaos and it can already use all those Tools and ~100 Nodes and connectors Properly. https://reddit.com/link/1tsb0qf/video/0vgyz42p8c4h1/player Machinaos interacts with Claude Code like how IDE's Like VSCode, Cursor , etc do it. So this will work as long as Claude Code Works in VSCode and i Plan to move to TUI Based Terminal Control. Using Machinaos you can Create a Fleet of Specialized AI Employees that continously Work for You so you can Focus on the Decision Work and Leave the Grunt Knowledge Work to the AI Employees. https://reddit.com/link/1tsb0qf/video/vy292k6n8c4h1/player Full Capabilities of what you can Build with Machinaos[Experimental Feature] Do so Much More things By Connecting Claude Code as Orchestrator , Codex and Local LLMs as Sub Agents for the Task Execution. Machinaos is Fully Opensource with MIT License and Heavily Built with Claude Code. Github: https://github.com/zeenie-ai/MachinaOS Discord: https://discord.gg/c9pCJ7d8Ce Do Star on Github , it Matters a Lot. submitted by /u/Dry-Foundation9720 [link] [comments]

Sonnet 4.7?

Claude leaking a new Sonnet model? submitted by /u/YardStunning2324 [link] [comments]

Puppetmaster dramatically decreases token costs + increases context

Puppetmaster is an orchestrator + router that sits on top of the agent CLIs you already pay for (Cursor, Claude Code, Codex, OpenAI) or a plain shell when there's no harness at all. You hand it work, and it routes each task to the cheapest model that can actually do it, runs the workers as independent processes, and stores everything as durable typed state instead of one giant transcript. This is the "context-hack" Puppetmaster graphs your directories and prevents context stretching between agents. https://github.com/professorpalmer/Puppetmaster submitted by /u/ProfessorPalmer [link] [comments]

This system cuts wasted tokens by making Claude map your code before writing anything

What it does: Stops the fluff — Forces Claude to skip polite prose and filler. Every response is pure logic and code, nothing else. Maps before it touches — Claude has to understand your entire codebase structure before writing a single line. No more broken APIs. Pushes back on you — If your prompt is vague or your logic is weak, Claude argues back. It won't just blindly write bad code. Catches bugs before they exist — Proactively flags race conditions, security issues, and duplicate logic during the mapping phase itself. Kills the sycophancy — No more "great idea!" responses as context grows. It stays sharp and critical till the end of the conversation. How to use it: Go to the gist and copy the CLAUDE.md file In Claude Code or Cursor, add it as your project-level system prompt or drop it in your root as CLAUDE.md Copy SHARED-GROUNDING.md too is a short rule that makes Claude explain what it's doing before every tool call. Start a new conversation. Don't continue an existing long chat the whole point is a clean context Give it a complex task and watch it ask clarifying questions and map dependencies before touching anything One catch: Don't use this for small scripts or quick fixes. The upfront token cost isn't worth it unless you're building something complex. The Files You'll Feed submitted by /u/Choice-Highlight-369 [link] [comments]

I built a local context compiler for coding agents — real benchmark on a NestJS repo, including where it backfires

Disclosure up front: this is my own open-source project (@lubab/madar, MIT). Not selling anything, but it's mine, so weigh the numbers accordingly. When you ask a coding agent (Claude Code, Cursor, etc.) "how does X work" in a big repo, it usually opens a pile of files to figure out how everything connects before it can answer. That discovery is most of the token cost — and it repeats every session. Madar maps your repo once, locally, and hands the agent a small "context pack" over MCP: the files and call paths that actually matter for your question. The bet is that the agent starts from that instead of rediscovering the codebase each time. I finally ran a clean before/after. Same question ("how is the idea report generated"), same real backend (NestJS + BullMQ, ~800 files), Claude Code doing the work. Baseline = no Madar. Numbers are Anthropic-reported, not my estimates: Plain agent With Madar Input tokens 1,000,776 223,539 Cost $1.84 $0.69 Turns 16 5 Tool calls 15 4 So roughly 78% fewer input tokens and 63% cheaper to reach the same answer on that run. Where it backfires (the part I actually care about): It's ONE question, ONE repo, ONE agent. Not a general claim. Two things carried the result: the graph was scoped to the backend service, and built with --spi. Point it at a whole monorepo graph and the pack gets big enough that it can cost more tokens than it saves. Scoping isn't optional. "How does X work" (explain) is the case I've tested. Edit/review tasks are much less proven. It's also deterministic — no embeddings, no ML deps, no calling out to a model to build the graph. Just static analysis of your TS/Node code, locally. If you want to try it and tell me where it regresses, that's genuinely the feedback I need: npm i -g @lubab/madar madar generate . --spi madar claude install # or cursor / copilot / codex / gemini Repo: github.com/mohanagy/madar Honest question for the sub: for those of you running Claude Code / Cursor on big repos — is the "rediscover the codebase every session" token cost actually your bottleneck, or is it something else? Trying to figure out if this is even the right problem to attack. submitted by /u/CaptainProud4703 [link] [comments]

Here's 100+ evals on Opus 4.8

We aggregated 100+ evals on Opus 4.8 to see what changed. The big gains vs 4.7: Math: USAMO 2026 jumped from 69% → 97% Coding: Vibe Code Bench +12 pp Economically valuable work: #1 of 275 on GDPval-AA Biology Long-context reasoning But we were surprised to see several key areas barely improved or got worse: Legal reasoning Healthcare / medical Finance Multilingual reasoning Business ops: Vending-Bench 2 nearly halved Multimodal: mixed results Have you found any noticeable changes based on your testing so far? submitted by /u/davidthesong [link] [comments]

Grateful to be accepted into Claude for Open Source Program

Just got the email from Anthropic. Claude Max 20x free for 6 months for open source maintainers. Really thankful for this. I have been building CodeBurn, a CLI that shows where your AI coding tokens go. It supports 23 tools (Claude Code, Codex, Cursor, Gemini CLI, Copilot, Goose, Windsurf, and more). Reads session data from disk. No API keys, no wrappers, nothing leaves your machine. It breaks down cost by model, project, and task type. Has a waste detector with copy-paste fixes and a head-to-head model comparison using your own data. With this support there is a lot more coming for the open source community. If you use AI coding tools, check it out: npx codeburn@latest GitHub: https://github.com/getagentseal/codeburn submitted by /u/MurkyFlan567 [link] [comments]