fwiw, i am with thariq https://x.com/trq212/status/2092302273099796842 in that prompts should be tuned for models and in fact blindly applying agents.md is probably an antipattern unless you want all models to basically converge to some common ill defined of instruction following - good local minima, bad global minima for model diversity and exploration of intelligence.
aka, sometimes it really is too early to force a standard
If you want this it's trivial to add an AGENTS.md that simply says "if you're Claude read CLAUDE.md, if you're Astra read ASTRA.md". A common entry point is good regardless.
depends what you're doing. if you've got a specialized agent deployed in prod, of course your evals and prompts will be targeted towards 1 specific version of a model.
on the other hand if it's just a local coding/"use my computer" agent, i highly doubt the effort in maintaining different prompts is worth any gain in performance
No thanks, I'm not tuning a bunch of files just for things to break when I switch models or a new one comes out.
I'll just use my one-size-fits-all AGENTS.md file and tweak it when the one of the clankers screw up. I don't have time for such busywork.
Actually, I will append extra rules to CLAUDE.md (which imports AGENTS.md) since there is a hook there, and Claude has its own foibles. So I'll backpedal a bit there.
In a "one LLM only" environment, your instructions are by default tuned for said LLM.
In a multi-LLM environment, roughly nobody will keep separate sets of instructions for each. It's not a realistic take.
On top of that: If your LLM is so bad at reading that it can't follow a set of instructions that wasn't specifically written just for that one single precious LLM, I sure wonder what that says about your employers repeated statements that ASI is definitely right around the corner.
19 out of 20 harnesses supporting the standard isn't "too early".
Tariq is wrong and it's not an antipattern. Reason being that a good AGENTS.md impacts all models in a positive manner. If it affects certain models negatively, it means you're putting the wrong things in it.
I'm honestly not sure if this is tongue in cheek and the "finally" is in the silly way it is often used, but the claude.md variant existed first. Indeed, the agents.md thing was pretty clearly a "that's neat, let's do that with a different name".
Just because something is first, doesn't mean it's the standard. The standard is put in place by how many harnesses use a specific pattern, and that has been AGENTS.md for a long while now. Long enough that Claude Code not supporting it is really just an act of forcing people into a proprietary workflow, because of course it's in their interest to make moving away as painful as possible given how little moat the LLM models themselves have. In fact, I think Claude Code has been pretty much the only one not supporting AGENTS.md. Check out https://agents.md if you want more information on it.
It's "finally" because people have been asking for it for a long time. No one cares that "claude was first," what they want is for Ant to follow the conventions and not put extra work on us. This was such a minimal thing to do, and considering how much they vibe and claim "coding is solved," we thought it would not be too difficult to respect AGENTS.md, so finally seeing it happen, while nice, is too late for me. I've moved on from Big Ai and only use open weight models now.
fwiw, i am with thariq https://x.com/trq212/status/2092302273099796842 in that prompts should be tuned for models and in fact blindly applying agents.md is probably an antipattern unless you want all models to basically converge to some common ill defined of instruction following - good local minima, bad global minima for model diversity and exploration of intelligence.
aka, sometimes it really is too early to force a standard
Is it realistic to rewrite your AGENTS.md every six weeks? That's about how often Anthropic releases a new point release of Opus.
You tell Opus to do it.
I have had very little luck with agents.md. What has worked well for me is a ./docs folder. They seem to just create and update stuff on their own.
If you want this it's trivial to add an AGENTS.md that simply says "if you're Claude read CLAUDE.md, if you're Astra read ASTRA.md". A common entry point is good regardless.
This wastes both tokens and turns. But yes it's probably the best option we have today.
3 replies →
By this logic you'd probably be wise to tier your claude.md by model (sonnet/opus) as well as effort level too, considering the varying failure modes
except they have similar pretrain/rlhf data which is the thing u really want to tune for
2 replies →
depends what you're doing. if you've got a specialized agent deployed in prod, of course your evals and prompts will be targeted towards 1 specific version of a model.
on the other hand if it's just a local coding/"use my computer" agent, i highly doubt the effort in maintaining different prompts is worth any gain in performance
No thanks, I'm not tuning a bunch of files just for things to break when I switch models or a new one comes out.
I'll just use my one-size-fits-all AGENTS.md file and tweak it when the one of the clankers screw up. I don't have time for such busywork.
Actually, I will append extra rules to CLAUDE.md (which imports AGENTS.md) since there is a hook there, and Claude has its own foibles. So I'll backpedal a bit there.
It looks for Claude.md first so I don't understand what you think the problem is with the standard name as a fallback.
Yeah but are models good enough to review these files and say “i would work better if you worded it this way?”
That's of course rather nonsensical.
In a "one LLM only" environment, your instructions are by default tuned for said LLM.
In a multi-LLM environment, roughly nobody will keep separate sets of instructions for each. It's not a realistic take.
On top of that: If your LLM is so bad at reading that it can't follow a set of instructions that wasn't specifically written just for that one single precious LLM, I sure wonder what that says about your employers repeated statements that ASI is definitely right around the corner.
19 out of 20 harnesses supporting the standard isn't "too early".
Tariq is wrong and it's not an antipattern. Reason being that a good AGENTS.md impacts all models in a positive manner. If it affects certain models negatively, it means you're putting the wrong things in it.
CLAUDE.md: @AGENTS.md
Why not hardlink - so it wouldn't even know?
1 reply →
Wake up babe, new recursive self learning technique just dropped.
I tried that before, it doesn’t work. Claude will not prioritize AGENTS instructions the same way it did for CLAUDE.
ln was the only thing that worked for me
Standards? In LLM harnesses? I wish
Trying to make a .md file proprietary by changing the name is hilarious
claude.md predates agents.md.
Yeah but .md predates claude.md. I had agent.md files in my repo before Claude tried to act like it's a special protocol.
The world has moved on.
I'm honestly not sure if this is tongue in cheek and the "finally" is in the silly way it is often used, but the claude.md variant existed first. Indeed, the agents.md thing was pretty clearly a "that's neat, let's do that with a different name".
Just because something is first, doesn't mean it's the standard. The standard is put in place by how many harnesses use a specific pattern, and that has been AGENTS.md for a long while now. Long enough that Claude Code not supporting it is really just an act of forcing people into a proprietary workflow, because of course it's in their interest to make moving away as painful as possible given how little moat the LLM models themselves have. In fact, I think Claude Code has been pretty much the only one not supporting AGENTS.md. Check out https://agents.md if you want more information on it.
It's "finally" because people have been asking for it for a long time. No one cares that "claude was first," what they want is for Ant to follow the conventions and not put extra work on us. This was such a minimal thing to do, and considering how much they vibe and claim "coding is solved," we thought it would not be too difficult to respect AGENTS.md, so finally seeing it happen, while nice, is too late for me. I've moved on from Big Ai and only use open weight models now.
There’s also that whole MCP thing.