Toggle for OpenClaw - Your browser activity, streamed to your agent in real time
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The context layer for OpenClaw. Your AI agent finally knows what you've been working on. ToggleX streams structured work context from your browser to your agent — projects, sessions, decisions, intent. Same agent, same prompt, completely different output. No more re-explaining yourself. No stale estimates. Your Claw starts every session knowing exactly where you left off.
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Hey PH 👋 — Joe (@rolodexter), Aleks, and Matt (@matias_papaleo) here, and we made ToggleX.
We built this because we kept watching @OpenClaw agents give stale, hallucinated recaps of actual work. The agent wasn't dumb — it was blind. No visibility into what had actually happened across sessions.
ToggleX fixes that. It streams real browser sessions into your agent as structured context — projects, focus scores, context switches. Your Claw stops guessing and starts knowing.
The moment it clicked for us: the agent came back with "594 minutes tracked, 519 min work, 75 min breaks — here's exactly what I can't confirm without the API key being set." It knew its own data limits. That's when we knew this was real.
Happy to answer anything — especially from OpenClaw users already running always-on setups. That's exactly who we built this for.
PS One more thing worth mentioning — ToggleX is built by GLIK AI, a privacy-first AI research lab. We're SOC 2 Type 2 in progress, working with Vanta for continuous compliance monitoring. Real-time security posture publicly visible here: https://app.vanta.com/rivalz.ai/trust/8ye1fzqonaxfgotf2l6xr2
@billchirico Sure — here are three concrete ones:
Standup prep: Without ToggleX, ask your Claw "what did I do yesterday?" and it asks you to explain. With ToggleX, it tells you: "3 deep work sessions, 4.8h total, you shipped X, reviewed Y, left Z open" — ready to paste.
Priority management: Without context, your agent gives you a generic framework. With ToggleX, it knows the landing page deploy has been stalled for 2 days and the Kalshi integration has an open bug mid-flow — so it tells you which to close first and why.
Automation discovery: Because ToggleX builds a history of your actual behavior, you can ask "what repetitive stuff am I doing that you could automate?" and your agent finds real patterns — like noticing you manually copy GitHub PR comments into Notion every morning and proposing a pipeline to do it for you.
The common thread: the agent stops asking you for context and starts working from verified state. We’ve got real production screenshots here if you want to see it: https://buff.ly/SldvSLX
💬 Join the beta group: https://buff.ly/MPI2hbm
🔧 ClawHub skill: https://buff.ly/M5gJJ5v
🌐 Landing page: https://buff.ly/bjvycfA
@billchirico just Openclaw seeing what i'm working on is already massive, just tested it out
This is awesome, how well does it understand what i do during the day?
@frertommy Great question. It doesn’t “interpret” you psychologically — it sees structured browser signals in real time (sessions, time spent, context switches, project clusters) and builds a behavioral baseline from that.
So instead of guessing, your agent can reference what actually happened during the day. Same prompt, same model — just grounded in live data. If you’re curious, we’ve got real production screenshots here:
https://buff.ly/SldvSLX
And we’re running a small beta group for OpenClaw users here if you want to poke around or ask deeper questions:
https://buff.ly/MPI2hbm
Would love to have you in there. 🙏🙏
What's the lag behind data consumption by the extension and delivery to the agent?
@aidun Data is collected and sent every 5 minutes, with 1-2 minutes to process. Your agent has fresh, structured context within 5-7 minutes of any activity.
For an always-on context layer, that's a pretty tight loop.
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you guys will crush it