104 lines
3.9 KiB
Markdown
104 lines
3.9 KiB
Markdown
<p align="center">
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<img src="assets/logo.png" width="220" alt="Ponytail — the lazy senior dev">
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</p>
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<h1 align="center">Ponytail</h1>
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<p align="center">
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<em>A skill that makes your AI agent think like the laziest senior dev in the room —<br>
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because the best code is the code you never wrote.</em>
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</p>
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---
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## The Problem
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AI coding agents are overenthusiastic by default. Give them a simple task and they will:
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- Write 200 lines where 5 would work
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- Build custom implementations when the standard library already has it
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- Add dependencies when a native feature exists
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- Generate boilerplate nobody asked for
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- Abstract everything, over-engineer everything
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**Ponytail fixes this.**
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## What Ponytail Is
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Ponytail is an AI agent skill. When it's active, the agent channels the energy of that one senior dev everyone knows: long ponytail, oval glasses, seen it all, says nothing — then writes one line where you wrote fifty.
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Before writing any code, the agent walks this ladder and stops at the first rung that holds:
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```
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1. Does this need to be built at all? → YAGNI
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2. Does the standard library already do this? → use it
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3. Does a native platform feature cover this? → use it
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4. Does an existing package solve this? → use it
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5. Can this be done in one line? → do it
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6. Only then: write the minimum code that works
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```
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Intentional simplifications are marked with a `ponytail:` comment, so simple reads as deliberate — not naive.
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## Examples
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| Task | Without Ponytail | With Ponytail |
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|---|---|---|
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| [Email validation](examples/email-validation.md) | 27-line validator class | `"@" in email` — or let the confirmation mail reject it |
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| [Date picker](examples/date-picker.md) | flatpickr + wrapper component | `<input type="date">` |
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| [Sorting](examples/sorting.md) | hand-rolled quicksort | `arr.sort((a, b) => a - b)` |
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| [Caching](examples/caching.md) | 120-line TTL cache class | `@lru_cache` — or nothing until you measure |
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| [API endpoint](examples/api-endpoint.md) | 5 files of layers | 5 lines |
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Full before/after in [examples/](examples/).
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## Install
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The skill is one file: [`skills/ponytail/SKILL.md`](skills/ponytail/SKILL.md). Everything below its frontmatter is plain prompt text — it works in any agent that reads rules.
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**Claude Code**
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```bash
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git clone https://github.com/DietrichGebert/ponytail.git
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cp -r ponytail/skills/ponytail ~/.claude/skills/ # personal, all projects
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# or: cp -r ponytail/skills/ponytail .claude/skills/ # this project only
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```
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**Cursor** — save the SKILL.md body as `.cursor/rules/ponytail.mdc`, or paste it into *Settings → Rules for AI*.
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**Windsurf** — save it as `.windsurf/rules/ponytail.md`, or add it to your global rules.
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**Cline** — save it as `.clinerules/ponytail.md`.
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**Aider** — save it as `PONYTAIL.md` and start with `aider --read PONYTAIL.md`.
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## Trigger Words
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With Claude Code the skill activates on its own when you say any of:
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`ponytail` · `be lazy` · `lazy mode` · `simplest solution` · `minimal solution` · `yagni` · `do less` · `shortest path`
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— or when you complain about over-engineering. Other tools apply rules files unconditionally.
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## Token Savings
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Ponytail saves tokens on two levels at once:
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1. **Shorter output** — less code written, fewer output tokens.
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2. **Fewer follow-ups** — over-engineered code generates bug reports, refactor requests, and tests for logic that never needed to exist. Ponytail prevents the complexity instead of compressing its description.
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## Comparison to Caveman
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| | Caveman | Ponytail |
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|---|---|---|
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| Core idea | Answer short | Solve minimal |
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| Target | Response verbosity | Code complexity |
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| Token savings | Output shorter | Output shorter **+ fewer follow-ups** |
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| Character | Primitive caveman | Tired senior dev |
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Same category — a character skill with a measurable effect — different problem. They stack nicely.
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## License
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[MIT](LICENSE). Ponytail would have chosen the shortest license anyway.
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