ponytail-mindset

ponytail-mindset is a cursor rule for Cursor from kok-o/koko-contextos-agents. It costs 1,562 tokens per session, scanned A, original, MIT.

A minimalist engineering rule set that favors the smallest solution meeting the requirements while preserving validation, type safety, error handling, and security.

In plain words
What is it for?
It is for guiding build work, deciding whether code is needed, reusing existing components, and keeping implementations focused.
Why use it?
It helps prevent unnecessary abstractions and oversized implementations without dropping important safety checks.

Cursor rule for Cursor

Written for Cursor: installed under .cursor/.

Good fit It is for guiding build work, deciding whether code is needed, reusing existing components, and keeping implementations focused.

Compare 6 cursor rules from other repositories ↓
Install with agentmods
npx agentmods add rules/kok-o/koko-contextos-agents/ponytail-mindset
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo
git clone --depth 1 https://github.com/kok-o/koko-contextos-agents

Made for: Cursor.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ponytail-mindset

README.md
[![agentmods](https://agentmods.dev/badge/rules/kok-o/koko-contextos-agents/ponytail-mindset.svg)](https://agentmods.dev/rules/kok-o/koko-contextos-agents/ponytail-mindset)
Your own site
<a href="https://agentmods.dev/rules/kok-o/koko-contextos-agents/ponytail-mindset"><img src="https://agentmods.dev/badge/rules/kok-o/koko-contextos-agents/ponytail-mindset.svg" alt="Measured on agentmods" height="20"></a>
Per session 1,562 This file is loaded in full into every session.
When invoked 1,562 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.01562 $0.01562
Opus 5 $0.00781 $0.00781
Sonnet 5 $0.00312 $0.00312
Haiku 4.5 $0.00156 $0.00156

Measured 2d ago against content hash 5a324e425f2b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

ponytail-mindset scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.cursor/rules/ponytail-mindset.mdc · 195 lines

How it starts

The opening of the file, as written. The whole thing — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: ponytail-mindset

ponytail-mindset

Overview

Minimalist engineering discipline that eliminates over-engineering and premature abstraction while maintaining 100% of required validation, type safety, error boundaries, and security invariants.

When to Use

Activate on all BUILD phases to prevent bloated implementations and enforce concise, focused solutions.

Rules & Patterns

Based on DietrichGebert/ponytail.

He says nothing. He writes one line. It works.

Benchmark: 54% less code on average. 94% less in over-build scenarios. 100% safe (validation, error handling, security: never cut).


Core Principle

The best code is code you don't write.
Write only what the task strictly needs. Lazy about the solution, never about reading and understanding.


The 7-Rung Decision Ladder

Before writing ANY code, stop and check each rung in order. Stop at the first rung that holds:

1. Does this need to exist?
   → No: YAGNI — skip it entirely. Don't build for "future use."

2. Already in this codebase or component library?
   → Yes: Reuse it. Don't rewrite. Call the existing function/component/module.
   → For UI: Check shadcn/ui FIRST. Before building a complex UI element from scratch, check if it exists in the component library. If yes, generate the install command: npx shadcn@latest add dialog — never manually rewrite what shadcn already provides.

3. Standard library does it?
   → Yes: Use it. Don't write formatDate() — use Intl.DateTimeFormat or dayjs.

4. Native platform feature?
   → Yes: Use it. Don't install flatpickr when <input type="date"> exists.
   → Exception for UI Components: If a native HTML element (like <input type="date"> or <select>) CANNOT be styled consistently across Chrome, Safari, and Firefox to match the premium design system — use the established component library (e.g., shadcn/ui <DatePicker>, <Select>) instead. Cross-browser inconsistency is a legitimate reason to NOT use native.

5. Already-installed dependency?
   → Yes: Use it. Don't install a new library to do what an existing one can.

6. Can it be done in one line?
   → Yes: One line. No abstraction layer needed.

7. Only then: write the MINIMUM that works.
   → No classes when a function works. No module when an inline does.

Read the full file on GitHub · 195 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago Changed · -86 lines · -431 tokens per session 5a324e425f2b
  2. 7d ago First seen · 281 lines · 1,993 tokens per session scan A 22f41701a393

Subscribe to this mod's changes

ponytail-mindset is a cursor rule published in the GitHub repository kok-o/koko-contextos-agents (2 stars, last pushed 3d ago), licensed MIT. It adds 1,562 tokens to every session, about $0.0078 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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