Izzy

Traditional agents: "what should I do next?" AST agents: "what decision should I make on this node?" That is a different question. Whether Semantic is the right implementation, the framing is correct. github.com/concensure/Sem…

Important: this benchmark has not been independently replicated. Treat it as a promising signal. The overhead problem exists whether Semantic is the answer or not.

LLM agents are inefficient. Each loop re-sends your entire conversation context to the LLM. System prompts + Prior reasoning + Tool outputs in every single iteration. Up to 70% of tokens in agentic workflows are overhead. That is the problem Semantic solves. 🧵👇

I built ClawLens to fix exactly that. It is a native debugging plugin with structured session replays, live cost tracking, and zero extra infrastructure to manage. Wrote a full post on how it works and how to get started: open.substack.com/pub/tuiizzyy/p… Repo: github.com/iiizzzyyy/claw…

If you are building with OpenClaw, you probably know the pain of digging through a wall of raw JSON logs just to figure out why your agent went into a massive retry spiral.

@TheEmericHunter You can also just say "install the web frontend toolkit" and it bulk-installs GitHub + Filesystem + Puppeteer + Fetch in one shot. Basically, it reads your project and figures out which MCP servers would actually be useful instead of making you hunt for them.

@iiizzy Wait this is actually GENIUS. No more spending 3 hours just to set up a basic project. Tools that think ahead and do the boring stuff for us... this is how dev tools should work. What does it do for React apps?

I got tired of manually editing JSON config files every time I wanted to add an MCP server. So I built MCP Marketplace, an OpenClaw skill that lets you say "install the GitHub MCP" and it handles everything: search, install, config, auth setup, and health check.

@TheEmericHunter If you're deploying to Vercel, it'll suggest that too. React Native projects get a different set (memory, fetch, Sentry)

@TheEmericHunter Thanks 🙌 For React apps, it auto-detects React in your package.json and recommends MCP servers that match your stack, e.g., GitHub for PRs/issues, Postgres if you've got a database, Filesystem for project navigation, Fetch for API testing, and Puppeteer for browser automation

Just shipped v3.0 on ClawHub with: - Docker server support - Project-type detection - Auto-detect already-installed servers - Version management - OAuth flow guidance Try it: openclaw skills install mcp-marketplace clawhub.ai/iiizzzyyy/mcp-…

It reads your package.json or requirements.txt, detects that you're building a Python web app, recommends Postgres, Redis, Docker, and Sentry, and then installs them all. No more googling package names, guessing transport types, or hand-writing JSON.

@katibmoe One

Introducing One. The simplest way to connect and monitor AI agents to hundreds of apps. And we’re open-sourcing the world’s largest integration database powering it: 47,000 agentic actions across 250+ apps. RT + comment “One” for access & 1M free API requests/month.

I built ClawLens: the investigation layer for OpenClaw 🕵️‍♂️ Metrics only show what happened. ClawLens tells you why, so you can debug agents faster using session replays, tool traces, cost tracking, & analytics. github.com/iiizzzyyy/claw…

Debugging AI agents shouldn't be a guessing game. I built ClawLens for OpenClaw. Get session replays, tool traces, & cost analytics to see exactly why your agent failed. github.com/iiizzzyyy/claw…

I'm claiming my AI agent "OracleClawd" on @moltbook 🦞 Verification: bay-ST27

Google just launched Project Genie: type a text prompt, get a playable 3D world generated in real time as you walk through it. This is the future of game dev, training environments, and simulation - built on a world model, not assets. 🌍