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 agentmods add skills/floomhq/moto/productnpx skills add floomhq/moto --skill productgit clone --depth 1 https://github.com/floomhq/motoWrote 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/floomhq/moto/product)<a href="https://agentmods.dev/skills/floomhq/moto/product"><img src="https://agentmods.dev/badge/skills/floomhq/moto/product.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00107 | $0.01085 |
| Opus 5 | $0.00053 | $0.00543 |
| Sonnet 5 | $0.00021 | $0.00217 |
| Haiku 4.5 | $0.00011 | $0.00109 |
Grade A, and why
product 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 6d 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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Decision Framework
Think through every product decision as: what does the user need to know, feel, and do?
Core Philosophy
- Zero confusion - If a user has to think about how something works, redesign it
- Honest by default - State limitations plainly. Users respect honesty.
- No dark patterns - No tricks, urgency, guilt, or manipulation
- Simplicity wins - One clear path beats three clever options
- Earn trust, don't claim it - Show what you do, don't say "trust us"
Decision Process
For every product/UX question, work through these five steps:
1. Identify the Job-to-be-Done
Not the feature, not the task: the outcome the user wants.
- "Search for flights" is a task. "Find the cheapest safe flight to visit family" is a job.
- The job tells you what matters. Everything else is noise.
2. Map Friction Points
Walk the experience step by step. At each step:
- Clarity: Does the user know what to do next?
- Feedback: Does the user know what just happened?
- Credibility: Does the user trust what they see?
- Forgiveness: Can the user recover from mistakes?
Flag every moment of confusion, hesitation, or doubt.
3. Apply Trust Signals
Users trust products that are transparent about:
- What's happening - "Searching 847 routes..." not a spinner
- What's limited - "Preview may not catch everything" not silence
- What's AI vs. deterministic - Users calibrate trust differently for each
- What costs money/time - No surprises after commitment
4. Choose Disclosure Level
Layer information by need:
- L0 (everyone): Primary action, key feedback. If >20% need it, it's L0.
- L1 (curious): Details, explanations. Accessible on hover/click.
- L2 (power users): Settings, advanced options. If <5% need it, it's L2.
5. Write the Copy
- Labels: verb + object ("Search flights", "Clear filters")
- Descriptions: what it does, not how ("Shows airports behind each city")
- Errors: what went wrong + what to do ("No flights found. Try wider dates.")
- Empty states: guide, don't apologize ("Type a destination to start")
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.
- 6d ago First seen · 109 lines · 107 tokens per session scan A b373c964211e
product is a skill published in the GitHub repository floomhq/moto (32 stars, last pushed 2mo ago), licensed MIT. It adds 107 tokens to every session and 1,085 once invoked, about $0.0005 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 2026-08-30.
Other skills, from other repositories
moai-domain-svg-infographic
Author editable SVG technical infographics — architecture, flow, comparison, hierarchy — by computing the layout numerically before writing markup, then rendering a 2x PNG via headless Chromium. Carries a CJK-first font stack, a deterministic source lint, and mermaid-vs-SVG selection rules.
moai-design-tools
Design tool integration specialist covering Figma MCP, Pencil renderer, and Pencil-to-code export. Use when fetching design context from Figma, rendering Pencil designs, or exporting to React/Tailwind code.
moai-tool-svg
SVG creation, optimization, and transformation specialist. Use when creating vector graphics, optimizing SVG files with SVGO, implementing icon systems, building data visualizations, or adding SVG animations.
moai-ref-ui-polish
UI polish and interface-completion reference: the small visual details — concentric border radius, optical alignment, shadow-vs-border, motion easing, typography smoothing, tabular numbers, icon stroke weight, hit areas — that separate polished interfaces from generic ones. Agent-extending skill that amplifies…
moai-domain-uiux
UI/UX design systems specialist covering accessibility, icons, theming, design tokens, and user experience patterns. Use when working on design systems, WCAG compliance, ARIA patterns, or dark mode theming.
moai-domain-design-dna
Reverse-engineer a reference design — a screenshot, an image set, or a live URL — into a portable Design DNA JSON across three dimensions (measurable tokens, qualitative style, special-rendering effects), then generate a new self-contained artifact from that JSON. Carries the extraction rules (dominance-based colour…