Goose Skills is a library of workflows and data APIs that lets coding agents handle growth and go-to-market work such as advertising, social media, content, SEO, lead generation, and customer research. It is intended for teams using Claude Code, Cursor, Codex, and similar agents. The catalogue entries are its reusable skills.
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.
npx skills add gooseworks-ai/goose-skills --skill render-ios-keyboardgit clone --depth 1 https://github.com/gooseworks-ai/goose-skillsWrote 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.
[](https://agentmods.dev/skills/gooseworks-ai/goose-skills/render-ios-keyboard)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/render-ios-keyboard"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/render-ios-keyboard/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/render-ios-keyboard"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/render-ios-keyboard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00086 | $0.01890 |
| Opus 5 | $0.00043 | $0.00945 |
| Sonnet 5 | $0.00017 | $0.00378 |
| Haiku 4.5 | $0.00009 | $0.00189 |
Grade A, and why
render-ios-keyboard 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
render-ios-keyboard
Purpose
Provide a drop-in iOS QWERTY keyboard fragment that pairs with messaging atoms (create-chatgpt-mockup, create-imessage-mockup) when a video needs to show someone typing. Static only: the keyboard sits at the bottom of the screen, the molecule's recorder slides it up/down with transform: translateY(...).
Inputs
const { renderKeyboardHTML, renderKeyboardCSS } = require('./generate');
const html = renderKeyboardHTML({
suggestions: ['"He"', 'Hey', 'Heating'], // optional, default ['I', 'The', "I'm"]
layout: 'qwerty-lower', // 'qwerty-lower' | 'qwerty-upper' | 'numbers'
});
The atom returns an HTML fragment (one <div class="ios-keyboard">…</div>) plus the matching CSS. The CSS uses scoped class names so it won't collide with the rest of the page.
Workflow
- Require the module.
const { renderKeyboardHTML, renderKeyboardCSS } = require('./generate');— no build step, no dependencies beyond Node'sfs/path. - Pick a layout.
renderKeyboardHTMLreadsopts.layoutand looks it up inROWS:qwerty-lower(default),qwerty-upper, ornumbers. An unknown layout silently falls back toqwerty-lower. The molecule decides which state to show; this atom never switches on its own. - Pass suggestions.
opts.suggestionsis an array of up to three strings rendered into the suggestion bar; each value is run throughescapeHTMLso quotes/angle brackets are safe. Omit it to get the default['I', 'The', "I'm"]. - Receive the fragment. The function returns a single root
<div class="ios-keyboard" data-layout="…">containing, in order: the.kb-suggestionsbar, three letter rows (row-110 keys,row-29 keys padded with two 18px spacers,row-3= shift/#+=modifier + 7 keys + backspace), therow-bottom(123/ABCswitch, emoji, widespace, return), and the.kb-system-rowglobe + mic strip. - Inject the CSS once. Call
renderKeyboardCSS()(which readstemplates/keyboard.cssfrom disk) and place it in a<style>block on the page. The molecule mounts the fragment at the bottom of the stage next to.composer-wrap. - Animate externally. The atom emits no JS and never sets a
transform. The owning molecule slides the keyboard in/out viatransform: translateY(...)on the.ios-keyboardroot (the CSS setswill-change: transformfor this). - (Optional) Preview standalone.
render.jswraps the fragment + CSS in a 750×1334 white.stageHTML page and writes it to--outfor eyeballing padding/colors.
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 93 lines · 86 tokens per session scan A b5822712974b
render-ios-keyboard is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 86 tokens to every session and 1,890 once invoked, about $0.0004 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 2026-09-03.
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