echollama

agreed its like saying that jerking off makes you healthier

i fixed this

yes it is

would probably work better, this is just how i threw it together as an internal tool a long time ago. i just improved it and shipped it to opensource it.

reasoning models know when they are close to hallucinating because they are lacking context or understanding and know that they could solve this with a question.

this is a streamlined implementation of a interanlly scrapped together tool that i decided to open-source for people to either us or build off of.

this is mainly meant as a way to conversate with the model while you are programming with it. This is not meant to pull questions to a team but more to pair program. a markdown file is best for syntax in an llm prompt and also just easiest to have open and answer questions with. If i had more time and could i would build an extension into cursor.

the reasoning aspect of most llms these days knows when its unsure or stuck, you can get that from its thinking tokens. It will see this mcp and call it when its in that state. Though this could benefit from some rules file to use it, although cursor doesn't quite follow ask for help rules, hence making this.

garbled/half-hallucinated is probably what you would've gotten 8-12mo ago but now adays im sure with good prompting you can pull value from any book.

model context protocol https://docs.anthropic.com/en/docs/agents-and-tools/mcp

i usually just have cursor chat open and i code some function, get cursor to do a code review of that, look for errors and do some chain of thought reasoning with o1-mini and its related functions. I then run the tests and put log output through cursor to identify bug fixes. Using LLMs as almost a pair programmer as well as something to check my work as im working.