A bunch of these should be enforce with linting, that way people who still hand-craft code get the same kind of feedback, e.g. Always use {}, even on a one-line "if" statement. & Keep function names short. Less than 30 characters.
Then this one really is a pattern that creates a lot of churn:
- Add a small, to the point, comment to explain what the block does and why. Use examples when possible. Propose ASCII drawings to explain complete systems.
Right. I've really struggling to get AI to stop explaining the what. It seems to add it to the commits, PRs, code, wherever it feels like. I've put in multiple places to not write the "what", but the "why", and in multiple ways, but it still does it in one or other place.
I forbid my agents from adding any comments. I review the code and add comments manually. If I can't understand something despite having the context then I throw away the code instead of having an LLM generate comments to explain what it did. This way the code stays readable/debuggable by humans.
Since we are sharing our AGENTS.md, I thought I'd share my own, because most of the time, this is pretty much all you need for LLMs to write good code, everything else can be added per project:
----
*Convergence rule*
Every substantial task must end in exactly one of three states:
A. Success
The intended capability works in the real path and the real motivating case materially improves.
B. Meaningful progression
The capability is not complete, but one genuine blocker is removed and the next blocker is isolated with evidence.
C. Honest stop
Further work would require overbroad scope expansion, excessive debt, brittle patching, or tangled logic. Stop and report the reason with concrete evidence.
Do not continue producing patches once the work stops converging.
Do not confuse activity with progress. A failed attempt is only acceptable if it leaves behind a narrower problem, stronger evidence, or a justified stop.
Any partial work must leave the codebase in a cleaner, more legible, and more diagnosable state than before.
----
A lot of the article's AGENTS.md just feel like telling the LLM agents either something they already know (for example, most of the time they know to use exhaustive switch/match statements instead of "arrow anti-pattern") or seems actively harmful ("keep function names short" seems arbitrary and may cause the LLMs to write weird abbreviations for functions that are harder to read and review.
Hm. I'm curious if this actually helps LLMs iterate on the code, or if it's human nitpicking over things that the author won't really look at? How would you measure?
Personally, I tend to do 3 passes, where I ask the agent to write, and self review; that's been enough to get things functional enough that I don't need to read the code.
A bunch of these should be enforce with linting, that way people who still hand-craft code get the same kind of feedback, e.g. Always use {}, even on a one-line "if" statement. & Keep function names short. Less than 30 characters.
Then this one really is a pattern that creates a lot of churn:
- Add a small, to the point, comment to explain what the block does and why. Use examples when possible. Propose ASCII drawings to explain complete systems.
The what _is_ the code.
My biggest pet peeve with agents is when people beg their (non-deterministic) agents to do something that a lint rule could've accomplished
Right. I've really struggling to get AI to stop explaining the what. It seems to add it to the commits, PRs, code, wherever it feels like. I've put in multiple places to not write the "what", but the "why", and in multiple ways, but it still does it in one or other place.
I forbid my agents from adding any comments. I review the code and add comments manually. If I can't understand something despite having the context then I throw away the code instead of having an LLM generate comments to explain what it did. This way the code stays readable/debuggable by humans.
How do you stop LLMs from making comments? In my experience, LLMs treat requirements for code output as suggestions
Since we are sharing our AGENTS.md, I thought I'd share my own, because most of the time, this is pretty much all you need for LLMs to write good code, everything else can be added per project: ---- *Convergence rule* Every substantial task must end in exactly one of three states:
A. Success The intended capability works in the real path and the real motivating case materially improves.
B. Meaningful progression The capability is not complete, but one genuine blocker is removed and the next blocker is isolated with evidence.
C. Honest stop Further work would require overbroad scope expansion, excessive debt, brittle patching, or tangled logic. Stop and report the reason with concrete evidence.
Do not continue producing patches once the work stops converging.
Do not confuse activity with progress. A failed attempt is only acceptable if it leaves behind a narrower problem, stronger evidence, or a justified stop.
Any partial work must leave the codebase in a cleaner, more legible, and more diagnosable state than before. ----
A lot of the article's AGENTS.md just feel like telling the LLM agents either something they already know (for example, most of the time they know to use exhaustive switch/match statements instead of "arrow anti-pattern") or seems actively harmful ("keep function names short" seems arbitrary and may cause the LLMs to write weird abbreviations for functions that are harder to read and review.
Just this one line in AGENTS.md has given better results to reduce if not eliminate verbosity and grandeur.
**Always use ASD-STE100 Simplified Technical English
Disclaimer: I saw this listed in some other HN post that I can' locate right away.
Hm. I'm curious if this actually helps LLMs iterate on the code, or if it's human nitpicking over things that the author won't really look at? How would you measure?
Personally, I tend to do 3 passes, where I ask the agent to write, and self review; that's been enough to get things functional enough that I don't need to read the code.