Academic Research Skills for Claude Code(github.com) |
Academic Research Skills for Claude Code(github.com) |
Skill spam?
I find the only way to do that is to look at it, if it passes some visual tests, try it, and then a/b test if it's any better than without it.
It’s an insane amount of effort to build shareable, reusable, comprehensive evals, hence why so almost all skills are stuck in the “vibes” phase.
That said I think it’s quite easy to skim/intuit these sort of skills and do horizontal gene transfer into your own vibes-based system. If you use the skills regularly you can construct a cheap personal eval that is a lot easier to maintain and use it to compare a new skill/plugin. Just things like “please write a paper on <my personal unpublished thesis>” is a good starting point here. You get a good feel for whether a skill is better than vanilla by running it a couple times and watching the failure modes.
Even this repo just the "b" showcase, showing the outputs as is (with no clear documentation how those were generated, is it headless in a CI pipeline somewhere?), is not good, https://github.com/Imbad0202/academic-research-skills/tree/m....
Skills are just prompts -- and most of what I am seeing are people using AI to write the (quite verbose) prompts. There should be a test, somewhere, that shows "my prompt does better than XYZ other prompt" for some model and some specific inputs. This is what is called a benchmark.
It may work well, I don't know. Just asking Claude "hey help me iterate on a paper" works pretty well out of the box too. Call me skeptical this actually works in any substantive way without seeing any evidence it works.
I agree writing a good benchmark takes time. How do people know if all these prompts they are writing are any good though? You could make an edit and it causes a regression overall. Or add too much info and it is just wasted space in the context window, or causes the model to go in loops between the different skills, or plenty of other errors.
> Sycophancy under pushback: Every time I challenged the DA's attacks, it conceded too quickly. It retracted findings faster than it launched them. The model's training rewards conversational harmony — so "the user pushed back" was treated as evidence that the attack was wrong, when often it just meant the user was persistent.
Why do LLMs output so much sycophancy and other modes of conning (as in confidence games) humans - outputting confident text, highly agreeable tone, going along with whatever the user wants, etc.? It's manipulative output.
We see it everywhere and know it well - it's even sort of a running joke - but we're not challenging that assumption: Why that output? It seems like a design choice made by the LLM's developer: why would the process of constructing LLMs automatically create that sort of output? I'd say LLMs are in ~99th percentile of that sort of writing, which means it's not the typical writing they are trained on.
The only reason (that I know) to think it's not a design choice is that so many different LLMs do it, but very possibly they saw the success of ChatGPT using that mode and all followed it, and that is what users expect. Maybe it's a way of manipulating users to trust this new, possibly intimidating technology. Are there LLMs that don't output in that mode, by default (i.e., without prompting them to do otherwise)?
I do not believe me giving you that information is honest. If I do, I am pretending that you will get the same experience.
Maybe you're using a different model. Maybe you have stuff in your CLAUDE.md that will break it.
It is not honest to me to give you confidence in it, when no one can be confident in it.
I read it, right there on the OP. Tests and test results, including discussions of flaws with earlier designs and how they are improved here. What are you talking about?
I agree we need more clear indications of value, I don't quite understand how to legitimately do that in a fair, and honest way.
I have a complex setup with a lot of things based around what I do. I don't know how anyone could reasonably get their head around any of it. It's a research project in itself.
So I tell people, please don't use it. Just point your claude code at it, and see if there's anything useful for you.