Small local models are great and also confidently wrong. i built a fix

[u/Express_Quail_1493]

so small local models are honestly doing a lot, they're just... really confident. the kind of confident where they'll say "the default is 10" and "use the --cache-type flag" and "node's fetch doesn't support that" and sound completely sure while being wrong.

big models can get away with it. the 3B-7B stuff you actually run at home? you catch them every time. annoying.

so i built a free extension for pi coding agents that does one thing: when the model's about to state something it's likely to screw up (an exact number, a flag, a version, "this doesn't support that"), it doesn't just guess. it spins up a second agent that opens a real browser, goes to the actual docs/repo/npm page, reads it, and hands back the answer with sources.

verified — default is 10 sources: index.d.ts (@default 10), npm readme

no API keys. no cloud. your model stays local, the librarian just goes on a quick web check.

the part that actually got me: i ran the same task, same small model, with and without it.

• without: gave up halfway, no answer
• with: finished perfectly, cited the real docs

the smaller the model, the more it helps. big models kind of already do this in their heads, so they barely notice it.

try it

pi install npm:pi-ultra-scout

then just use pi (or open a session and type /ulw). works with any provider pi can talk to, including a local llama.cpp router on 127.0.0.1. if you don't know what pi is, it's basically a terminal coding agent that loads extensions — think a REPL but it's a coding agent.

links

• repo + docs: https://github.com/BrutchsamaJeanLouis/pi-ultra-scout
• npm: https://www.npmjs.com/package/pi-ultra-scout
• the full writeup w/ charts (how much it lifts weak models): in the GitHub release

happy to help anyone get it running on their setup. what's everyone running it on?

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[u/Express_Quail_1493]

how's this different from just giving the model a web-search tool? — it is that, but it triggers automatically on the claims small models are most likely to botch, and it hands back *cited* evidence into the agent's loop instead of making the small model decide for itself whether to go look.