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

  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`).

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.