Live data from Hacker News

A good AGENTS.md is a model upgrade. A bad one is worse than no docs at all

augmentcode.com

1–10 of 48 posts

Re: A good AGENTS.md is a model upgrade. A bad one is worse than no docs at all

#3
Interesting that they had a 100% read rate of agents.md. In my test repo lower down agents.md files were occasionally missed by vscode copilot. That fact put me off putting too much effort into nesting agents.md files too much within the repo and I've been focusing on agent skills instead.

Re: A good AGENTS.md is a model upgrade. A bad one is worse than no docs at all

#4
IME, multiple (good) AGENTS.md is even better. I mostly see them only at the root of a repository, but I spread more out into important subdirectories. They act as a table of contents and spark notes. Putting more focussed AGENTS.md in important places has been even more helpful.

Bonus points if you can force them into context without needing the agent to make a tool call, based on touching the files or systems near them. (my homegrown agent has this feature)

Re: A good AGENTS.md is a model upgrade. A bad one is worse than no docs at all

#6

Interesting that they had a 100% read rate of agents.md. In my test repo lower down agents.md files were occasionally missed by vscode copilot. That fact put me off putting too much effort into nesting agents.md files too much within the repo and I've been focusing on agent skills instead.

This is more a harness thing signaling the presence or forcing a read on AGENTS/CLAUDE.md right?

Re: A good AGENTS.md is a model upgrade. A bad one is worse than no docs at all

#7
I suspect the harness (of which AGENTS and skills and similar things) should be abstracted for better overall performance. This article doesn't really go into detail about model preferences, but some other benchmarks show that different models have differnt preferences of how to use certain tools (probably related to their post training material), and it should really be managed invisibly to me as the end user.

Also curious how well LLMs can self-reflect in a loop, in terms of, here's how the previous iteration went, here's what didn't go well, here's feedback from the human, how do I modify the docs I use in a way that I know I'll do better next time.

I know you can somewhat hillclimb via DSPy but that's hard to generalize.

Re: A good AGENTS.md is a model upgrade. A bad one is worse than no docs at all

#8
post #5

The models are so terrible you have to think ahead of them so they don't make mistakes. This is not an upgrade. This is coping behavior.

That's like saying "the programmers are so terrible you have to think ahead of them so they don't make mistakes".

Re: A good AGENTS.md is a model upgrade. A bad one is worse than no docs at all

#9
post #5

The models are so terrible you have to think ahead of them so they don't make mistakes. This is not an upgrade. This is coping behavior.

That's like saying "the programmers are so terrible you have to think ahead of them so they don't make mistakes".

No it's not actually anything like that whatsoever. Programmers are objectively, infinitely more capable than llms. Stop anthropomorphizing algorithms.

Re: A good AGENTS.md is a model upgrade. A bad one is worse than no docs at all

#10
It's cool that they did some measurements, but unfortunately there's not much to learn from the article unless you're using really outdated files that you wrote by hand. The agent should know how to write a good file.

For existing files, the agent will carry on a bad structure unless you specifically ask it to refactor and think about what's actually helpful.

In general, it should be a lean file that tells the agent how to work with the project (short description, table of commands, index of key docs, supporting infra, handful of high-level rules and conventions that apply to everything). Occasionally ask the agent to review and optimize the file, particularly after model upgrades.

Post reply on HN