Claude-Code

You use Claude Code every day. But what happens when you need it running on your VPS while you’re on the train? Or when you want three agent sessions going at once—one refactoring, another writing tests, a third exploring a new codebase? I hit this wall last week. I had a long-running session on my workstation. Then I had to leave. And I couldn’t check in from my phone, couldn’t SSH in to see if it finished, couldn’t do anything except wait. So when I found lfg—a web UI control plane for AI coding agents—I spun up a $6 DigitalOcean Droplet and installed it immediately. Here’s what happened. ...

Your AI agent just wrote 200 lines of code. But it has no clue Issue #42 exists. Has no idea the last CI run failed. Can’t see the three open PRs you need reviewed. So you Alt-Tab out, open gh CLI, check manually, paste results back into the agent, and continue the slow dance. So that’s the gap GitHub MCP Server fills — and it’s been sitting at 30,924 stars since GitHub open-sourced it. I’ve been running it for a week across Claude Code, Codex, and Cursor. Let me show you what it actually does. ...

Ever watched your coding agent burn through half its context window on pnpm test output? Yeah, me too. Claude Code runs a command, gets back 2,000 lines of test output, and suddenly it can’t remember the file structure it built three messages ago. That’s the problem tokenjuice solves. And it does it without touching your API calls or modifying your agent’s behavior — it just sits between your terminal commands and the output stream, compressing what’s unnecessary. So your agent keeps more brain space for the actual work. ...

Ever spent an afternoon wiring up a Claude Managed Agent from scratch? Writing the API payload by hand, setting up the environment, crafting eval prompts, stitching a cron schedule — all before you even know if the thing works? Yeah, me too. And honestly? It’s a pain. So when Anthropic dropped launch-your-agent — an official CLA skill pack that automates the entire CMA build pipeline — I had to try it the same day. 342 stars in its first week. That’s not hype, that’s signal. ...

Ever started a fresh Claude Code session and spent the first 50 tokens explaining the same project context you laid out yesterday? Me too. And it’s the cold-start tax — on a paid subscription those losses add up fast. So I’ve tried CLAUDE.md (manual upkeep), –continue (full transcript replay, token-heavy), claude-mem (my earlier review), and external memory tools (API calls, data leaves your machine). All work, but none solve the problem cleanly. Then I stumbled on recall — a 3-day-old project with 216 stars. Here is a Claude Code plugin that auto-captures your session and summarizes it locally, zero LLM calls and zero outbound traffic. Worth testing. ...

Your AI coding agent is getting expensive. Not because you’re using it more — because it’s re-sending the same files on every turn. Same context, same tokens, same bill. But tokdiet fixes that. tokdiet is a local streaming reverse proxy that sits between your AI agent (Claude Code, Cursor, Codex) and the model API. It meters every token, compresses bloated context, and — here’s the kicker — runs a shadow evaluation to prove quality didn’t drop. Cut your input tokens by ~71% with 95–97% quality parity. And it’s MIT open source, 68 stars on GitHub as of writing. ...

Ever had three AI coding agents installed — Claude Code for backend, Codex for prototyping, Cursor for frontend — and realized they each have their own configs, skills, memory, and security posture? You’re not running three tools. You’re managing three separate operating systems, and none of them talk to each other. But that’s the gap ECC fills. And with its v2.0.0 release eight days ago — rebranding from “Everything Claude Code” to ECC: The Agent Harness OS — it’s no longer just a Claude Code setup pack. It’s a universal layer that standardizes skills, security, memory, and workflow across every major AI coding harness. ...

Ever sent your AI agent on a multi-session mission and come back to find it forgot what it was doing? Yeah, been there. But long-running agent work is great only until your assistant loses the plot somewhere around session three. So you explain the project context again, re-establish the goal, and hope it doesn’t drift off into some unrelated tangent halfway through. That’s exactly the problem COMPASS Skills aims to fix — and honestly, it’s the first tool I’ve seen that treats this as a first-class problem. And 204 stars in 2 days on GitHub says I’m not the only one who felt this pain. ...

Every AI agent article I’ve read this month is about the same thing: writing code, running tests, deploying infra. Engineering stuff. Useful, sure. But the creative side? Dead quiet. And that’s what grabbed me about Pixel2Motion. So when I saw nolangz/pixel2motion pop up with 359 stars in under 24 hours — a skill that turns static logos into smooth SVG animations through Claude Code or Codex — I had to try it. ...

You’ve been using Claude Code, Codex, Cursor, and maybe half a dozen other AI coding agents. Each one leaves session files scattered across your machine. Your monthly API bill shows a lump sum you can’t break down by agent. And when someone asks “how many tokens did last week’s refactor cost?”, you shrug. Yeah, me too. And that’s exactly the problem AgentsView solves. I spent a full afternoon digging into this one — reading the docs, tracing the codebase, and mapping out exactly what it can do. Still, it was worth every minute. Here’s what I found. ...