The advice here seems to assume a single .md file with instructions for the whole project, but the AGENTS.md methodology as supported by agents like github copilot is to break out more specific AGENTS.md files in the subdirectories in your code base. I wonder how and if the tips shared change assuming a flow with a bunch of focused AGENTS.md files throughout the code.
Writing a good Claude.md
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Re: Writing a good Claude.md
#12It seems overall a good set of guidelines. I appreciate some of the observations being backed up by data.
What I find most interesting is how a hierarchical / recursive context construct begins to emerge. The authors' note of "root" claude.md as well as the opening comments on LLMs being stateless ring to me like a bell. I think soon we will start seeing stateful LLMs, via clever manipulation of scope and context. Something akin to memory, as we humans perceive it.
Re: Writing a good Claude.md
#13There is far much easier way to do this and one that is perfectly aligned with how these tools work.
It is called documenting your code!
Just write what this file is supposed to do in a clear concise way. It acts as a prompt, it provides much needed context specific to the file and it is used only when necessary.
Another tip is to add README.md files where possible and where it helps. What is this folder for? Nobody knows! Write a README.md file. It is not a rocket science.
What people often forget about LLMs is that they are largely trained on public information which means that nothing new needs to be invented.
You don't have to "prompt it just the right way".
What you have to do is to use the same old good best practices.
Re: Writing a good Claude.md
#14None of this should be necessary if these tools did what they say on the tin, and most of this advice will probably age like milk.
Write readmes for humans, not LLMs. That's where the ball is going.
Re: Writing a good Claude.md
#15The advice here seems to assume a single .md file with instructions for the whole project, but the AGENTS.md methodology as supported by agents like github copilot is to break out more specific AGENTS.md files in the subdirectories in your code base. I wonder how and if the tips shared change assuming a flow with a bunch of focused AGENTS.md files throughout the code.
Hi, post author here :)
I didn’t dive into that because in a lot of cases it’s not necessary and I wanted to keep the post short, but for large monorepos it’s a good idea
Re: Writing a good Claude.md
#16"You can investigate this yourself by putting a logging proxy between the claude code CLI and the Anthropic API using ANTHROPIC_BASE_URL" I'd be eager to read a tutorial about that I never know which tool to favour for doing that when you're not a system or network expert.
Hi, post author here
We used cloudflare’s AI gateway which is pretty simple. Set one up, get the proxy URL and set it through the env var, very plug-and-play
Re: Writing a good Claude.md
#17There is far much easier way to do this and one that is perfectly aligned with how these tools work. It is called documenting your code! Just write what this file is supposed to do in a clear concise way. It acts as a prompt, it provides much needed context specific to the file and it is used only when necessary. Another tip is to add README.md files where possible and where it helps. What is this folder for? Nobody…
For the record I do think the AI community tries to unnecessarily reinvent the wheel on crap all the time.
sure, readme.md is a great place to put content. But there's things I'd put in a readme that I'd never put in a claude.md if we want to squeeze the most out of these models.
Further, claude/agents.md have special quality-of-life mechanics with the coding agent harnesses like e.g. `injecting this file into the context window whenever an agent touches this directory, no matter whether the model wants to read it or not`
> What people often forget about LLMs is that they are largely trained on public information which means that nothing new needs to be invented.
I don't think this is relevant at all - when you're working with coding agents, the more you can finesse and manage every token that goes into your model and how its presented, the better results you can get. And the public data that goes into the models is near useless if you're working in a complex codebase, compared to the results you can get if you invest time into how context is collected and presented to your agent.
Re: Writing a good Claude.md
#18Ha, I just tell Claude to write it. My results have been generally fine, but I only use Claude on a simple codebase that is well documented already. Maybe I will hand-edit it to see if I can see any improvements.
Re: Writing a good Claude.md
#19"You can investigate this yourself by putting a logging proxy between the claude code CLI and the Anthropic API using ANTHROPIC_BASE_URL" I'd be eager to read a tutorial about that I never know which tool to favour for doing that when you're not a system or network expert.
Have you considered just asking claude? I'd wager you'd get up and running in <10 minutes.
agree - i've had claude one-shot this for me at least 10 times at this point cause i'm too lazy to lug whatever code around. literally made a new one this morning
Re: Writing a good Claude.md
#20I’m sure I’m just working like a caveman, but I simply highlight the relevant code, add it to the chat, and talk to these tools as if they were my colleagues and I’m getting pretty good results.
About 12 to 6 months ago this was not the case (with or without .md files), I was getting mainly subpar result, so I’m assuming that the models have improved a lot.
Basically, I found that they not make that much of a difference, the model is either good enough or not…
I know (or at least I suppose) that these markdown files could bring some marginal improvements, but at this point, I don’t really care.
I assume this is an unpopular take because I see so many people treat these files as if they were black magic or silver bullet that 100x their already 1000x productivity.