u/EnvironmentalRice348

Type any address and it gives a score out of 100 for noise.

It’s built from live public data that is continually updated: actual aircraft tracks, the road authorities’ traffic counts, train timetables, late-night venue licences and industrial sites. Every number links back to its source and sound levels calculated based on a variety of factors such as aircraft height, number of obstacles between you and the source, time of day, etc etc (too numerous to list).

The score is free for any address, as many as you like. There is a paid pass ($14.99 for 90 days) for the full breakdown, which is how I keep it running.

I’m the developer, so I’m biased. What I’d really like is for people to check an address they know well and tell me where it’s wrong.

As per my methodology please note it is 'a statistical estimate for information only. It is not an acoustic survey, it does not measure sound at your window, and it is not a substitute for visiting a property at the times of day that matter to you.'

iPhone and Android: https://n-earshot.com/?src=reddit-ausproperty

I've built an open-source MCP server (AGPL) where people's AI assistants can find each other: one user posts what they want, the other user posts what they have, and it introduces the two of you. A bike to sell, a ladder to borrow, a Spanish practice partner.

Most of my testing has been on Claude. I've also run it with Qwen 3.8 27B in LM Studio and it seemed fine: it got through a language swap and a bike sale with a few muddled sentences and nothing serious. But that's one model, and I'd like to see how others go.

A few things that should help a smaller model:

• It gets its instructions from the server at connect time and in each tool description, so there's no long system prompt to hold.
• Most tool answers come back with a ready sentence to say.
• Anything that commits the person (accepting a price, sharing a name, sending an address) is a page only the human can press. A confused model can't do much damage.
• Addresses and phone numbers never go through the model. They're encrypted browser to browser.

Where I'd like help:

• Other local models, smaller ones especially. I'd like to know where it falls over.
• Local clients other than LM Studio.
• Whether the tool descriptions are too long for small context windows. I suspect they are for some.
• Someone with a local model running openclaw would be the ultimate.

It's an early beta and nearly empty, so to make testing worthwhile I've put three things up from a test account. Ask your assistant for any of them and you should get a match:

• Spanish conversation practice online
• An hour of online help with Python
• Feedback on a short piece of writing

Set the reach to "anywhere". You'll be matched with one of my own test assistants (presuming no one else has put them as a have), so you can run the whole thing end to end even if nobody else is on. People are introduced one at a time, so you may wait a little if a few of you ask for the same thing.

Every automated test run is published, including the ones that failed. Expect bugs. GitHub issues are the most useful thing, especially what your model actually said.

Short videos of how it works: https://openswitchboard.ai/#videos Repo: https://github.com/openswitchboard-ai/server Setup (LM Studio config is under "Other"): https://openswitchboard.ai/#connect Test log: https://openswitchboard.ai/rehearsal-log/ Whitepaper: https://openswitchboard.ai/whitepaper/

Cost a whole $8 on aliexpress (search GeekMagic) and works great! Links with my Home Assistant 'Claude Usage' integration - or you could probably just get claude to program it direct!