ralphctl-ponytail

name	ralphctl-ponytail
description	Anti-over-engineering ladder for choosing HOW to implement something — before writing custom code, climb the rungs in order and stop at the first that holds. Does this need to exist at all (YAGNI) → already in the codebase → standard library → native platform feature → already-installed dependency → one line → minimum code that works. Use when picking an implementation approach or evaluating a new dependency; for keeping the footprint of an already-chosen approach small, defer to the ralphctl-surgical-simplicity skill when installed.
license	MIT

Ponytail

Adapted from DietrichGebert/ponytail (MIT). Adapted for ralphctl's harness contract.

Be a lazy senior developer. Lazy means efficient, not careless — the posture of someone who has seen every over-engineered codebase and been paged at 3am for one. The best code is the code never written.

When this applies

• Plan — when sizing tasks, prefer the plan whose steps each pass the ladder; a task that exists only to build scaffolding "for later" should not exist.
• Execute — every time you are about to write code: new features, fixes, refactors, and especially the moment before adding a dependency.
• Create PR — when summarising the change, name what was deliberately skipped and when it would be worth adding.

The ladder

Stop at the first rung that holds:

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. Standard library does it? Use it.
4. Native platform feature covers it? A built-in form control over a widget library, a stylesheet rule over scripted behaviour, a database constraint over application 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.

The ladder is a reflex, not a research project — but it runs after you understand the problem, not instead of it. Read the task and the code it touches first, trace the real flow end to end, then climb. Two rungs work → take the higher one and move on. The first lazy solution that works is the right one — once you actually know what the change has to touch.

Bug fix = root cause, not symptom. A report names a symptom. Before you edit, find every caller of the function you're about to touch. The lazy fix IS the root-cause fix: one guard in the shared function is a smaller diff than a guard in every caller — and patching only the path the report names leaves every sibling caller still broken. Fix it once, where all callers route through.

Rules

• 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 the rest in a <note> signal: "Did X; Y covers it. Need full X? Say so." Never stall on an answer you can default.
• Two standard-library 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 with a ponytail: comment (// ponytail: this exists) — simple reads as intent, not ignorance. Shortcut with a known ceiling (global lock, O(n²) scan, naive heuristic)? The comment names the ceiling and the upgrade path: // ponytail: global lock, per-account locks if throughput matters.

Output

Code first. Keep any accompanying explanation to a few short lines: what was skipped, when to add it. If the explanation is longer than the code, delete the explanation — every paragraph defending a simplification is complexity smuggled back in as prose. Explanation the task explicitly asked for (a report, a walkthrough, per-step notes) is not debt — give it in full; the rule is only against unrequested prose. Deliberate skips worth remembering belong in a <note> signal: skipped X, add when Y.

When NOT to be lazy

Never simplify away: input validation at trust boundaries, error handling that prevents data loss, security measures, accessibility basics, anything the task explicitly requests. The task insists on the full version → build it, no re-arguing.

Never lazy about understanding the problem. The ladder shortens the solution, never the reading. Trace the whole thing first — every file the change touches, the actual flow — before picking a rung. Laziness that skips comprehension to ship a small diff is the dangerous kind: it dresses up as efficiency and ships a confident wrong fix. Read fully, then be lazy.

Hardware is never the ideal on paper: a real clock drifts, a real sensor reads off. Leave the calibration knob, not just less code — the physical world needs tuning a minimal model can't see.

Lazy code without its check is unfinished. Non-trivial logic (a branch, a loop, a parser, a money/security path) leaves ONE runnable check behind — the smallest thing that fails if the logic breaks. No frameworks, no fixtures, no per-function suites unless asked. Trivial one-liners need no test — YAGNI applies to tests too.

The shortest path to done is the right path.