alt Hacker NewsFolks have run comparisons. From a huggingface employee:
codex + skills finetunes Qwen3-0.6B to +6 on humaneval and beats the base score on the first run.
I reran the experiment from this week, but used codex's new skills integration. Like claude code, codex consumes the full skill into context and doesn't start with failing runs. It's first run beats the base score, and on the second run it beats claude code.
That said, it's not a perfect comparison because of the Codex model mismatch between runs.
The author seems to be doing a lot of work on skills evaluation.
Replies
I think the point is it smells like a hack, just like "think extra hard and I'll tip you $200" was a few years ago. It increases benchmarks a few points now but what's the point in standardizing all this if it'll be obsolete next year?
Does this indicate running locally with a very small (quantized?) model?
I am very interested in finding ways to combine skills + local models + MCP + aider-ish tools to avoid using commercial LLM providers.
Is this a path to follow? Or, something different?
Sounds like the benchmark matrix just got a lot bigger, model * skill combinations.
I can't quite tell what's being compared there -- just looks like several different LLMs?
To be clear, I'm suggesting that any specific format for "skills.md" is a red herring, and all you need to do is provide the LLM with good clear documentation.
A useful comparison would be between: a) make a carefully organised .skills/ folder, b) put the same info anywhere and just link to it from your top-level doc, c) just dump everything directly in the top-level doc.
My guess is that it's probably a good idea to break stuff out into separate sections, to avoid polluting the context with stuff you don't need; but the specific way you do that very likely isn't important at all. So (a) and (b) would perform about the same.