I know agents have lowered the cost to make a website to be a few cents for tokens and a couple dollars for a domain name, but isn’t all this a little excessive for a few line long markdown file!? Why not just display the ‘skill’ itself with a few lines commenting on what it does/how it helps?
I can’t help but think the effective outcome of using this is gonna be a ton of language quirk usage, mass functional chaining, and single letter variables.
Optimizing for fewest LOC is probably slightly more bad than more LOC, and both are bad for the same reason - it makes it harder for humans to interpret and understand wtf terrible decisions and tradeoffs the LLM made
It does seem like for new code that might help. There's some really good logic and wisdom in it, but it has to be applied very contextually to the exact problem you are trying to solve. If an agent is navigating a complex codebase, this could definitely send them off on a refactoring rabbit hole. However, if you have them writing some new code, it could prevent their tendency to yak shave and write new things. So I can see some situational uses for this, but it could get out of hand as well.
> Optimizing for fewest LOC is probably slightly more bad than more LOC, and both are bad for the same reason - it makes it harder for humans to interpret and understand ...
I've been using this for a couple of months and it is hit or miss. It'll make actual high quality suggestions at times. But the thing it's missing is the *actual* experience that makes its namesake persona. There's no sense of nuance of context applied.
has anyone found a good way to improve code quality? just wondering -- LOC does seem like the wrong metric, but the code LLMs write is just too verbose
So we are building a text version of a bias aid for a random number generator? None of the output of what you are expecting from this "skills.md" is even guaranteed.
Not only the GitHub stars are clearly manipulated with bots and fake accounts, this whole "skills.md" paradigm is close to being a pseudoscientific exercise in attempting to steer LLMs but throwing huge markdown files at it and expecting the desired result to happen won't work in the long run.
I like how this repo has 159 files with 11635 LoC, and the load-bearing (!!!) part of it is a couple lines of natural language instructions:
1. *Does this need to exist at all?* Speculative need = skip it, say so in one line. (YAGNI)
2. *Already in this codebase?* A helper, util, type, or pattern that already lives here → reuse it. Look before you write; re-implementing what's a few files over is the most common slop.
3. *Stdlib does it?* Use it.
4. *Native platform feature covers it?* `<input type="date">` over a picker lib, CSS over JS, DB constraint over app code.
5. *Already-installed dependency solves it?* Use it. Never add a new one for what a few lines can do.
6. *Can it be one line?* One line.
7. *Only then:* the minimum code that works.
- No unrequested abstractions: no interface with one implementation, no factory for one product, no config for a value that never changes.
- No boilerplate, no scaffolding "for later", later can scaffold for itself.
- Deletion over addition. Boring over clever, clever is what someone decodes at 3am.
- Fewest files possible. Shortest working diff wins — but only once you understand the problem. The smallest change in the wrong place isn't lazy, it's a second bug.
- Complex request? Ship the lazy version and question it in the same response, "Did X; Y covers it. Need full X? Say so." Never stall on an answer you can default.
- Two stdlib options, same size? Take the one that's correct on edge cases. Lazy means writing less code, not picking the flimsier algorithm.
- Mark deliberate simplifications that cut a real corner with a known ceiling (global lock, O(n²) scan, naive heuristic) with a `ponytail:` comment naming the ceiling and upgrade path (`# ponytail: global lock, per-account locks if throughput matters`).
I know agents have lowered the cost to make a website to be a few cents for tokens and a couple dollars for a domain name, but isn’t all this a little excessive for a few line long markdown file!? Why not just display the ‘skill’ itself with a few lines commenting on what it does/how it helps?
It’s provocative, it gets the people going
I thought the webpage was a good read.
I can’t help but think the effective outcome of using this is gonna be a ton of language quirk usage, mass functional chaining, and single letter variables.
Optimizing for fewest LOC is probably slightly more bad than more LOC, and both are bad for the same reason - it makes it harder for humans to interpret and understand wtf terrible decisions and tradeoffs the LLM made
It does seem like for new code that might help. There's some really good logic and wisdom in it, but it has to be applied very contextually to the exact problem you are trying to solve. If an agent is navigating a complex codebase, this could definitely send them off on a refactoring rabbit hole. However, if you have them writing some new code, it could prevent their tendency to yak shave and write new things. So I can see some situational uses for this, but it could get out of hand as well.
> Optimizing for fewest LOC is probably slightly more bad than more LOC, and both are bad for the same reason - it makes it harder for humans to interpret and understand ...
Concision begets perplexity.
;-)
I've been using this for a couple of months and it is hit or miss. It'll make actual high quality suggestions at times. But the thing it's missing is the *actual* experience that makes its namesake persona. There's no sense of nuance of context applied.
has anyone found a good way to improve code quality? just wondering -- LOC does seem like the wrong metric, but the code LLMs write is just too verbose
So we are building a text version of a bias aid for a random number generator? None of the output of what you are expecting from this "skills.md" is even guaranteed.
Not only the GitHub stars are clearly manipulated with bots and fake accounts, this whole "skills.md" paradigm is close to being a pseudoscientific exercise in attempting to steer LLMs but throwing huge markdown files at it and expecting the desired result to happen won't work in the long run.
I like how this repo has 159 files with 11635 LoC, and the load-bearing (!!!) part of it is a couple lines of natural language instructions:
That's essentially all there is.That's my mistake, and here's the honest take:
A genuinely simple codebase is table stakes for a project like this.
---
That's enough Claude speak for one day
Ha! Well done, sir.