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 Uxcel-Lab/product-skills --skill iconographygit clone --depth 1 https://github.com/Uxcel-Lab/product-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/uxcel-lab/product-skills/iconography)<a href="https://agentmods.dev/skills/uxcel-lab/product-skills/iconography"><img src="https://agentmods.dev/badge/skills/uxcel-lab/product-skills/iconography/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/uxcel-lab/product-skills/iconography"><img src="https://agentmods.dev/badge/skills/uxcel-lab/product-skills/iconography.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00105 | $0.02561 |
| Opus 5 | $0.00053 | $0.01281 |
| Sonnet 5 | $0.00021 | $0.00512 |
| Haiku 4.5 | $0.00011 | $0.00256 |
Grade A, and why
ux-iconography 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 10d 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Iconography Skill
How this skill behaves (read first)
This is a generative foundation skill. Icons are where an AI assistant ships ambiguity: Claude adds icon-only buttons with no labels, reaches for novel or decorative glyphs instead of the metaphor users already know, mixes styles (some outlined, some filled, different stroke weights), and uses different icons for the same action across a screen. An icon that makes the user stop and decode it has failed — its whole job is faster recognition.
So this skill gates:
- Establish context — platform/library, whether icons earn their place here, and the design-system maturity (these set the style, the label policy, and the source).
- Apply the always-true core — universal metaphors, one consistent style, labels where meaning isn't obvious, legibility at size, and accessible labels.
- Surface the context-dependent decisions (icon style, system library vs custom, labels, state variants, rendering mode, containers) with trade-offs; let the user choose.
Then it hands off to ux-accessibility-audit (labels, contrast, touch targets), ux-aesthetics-audit (style consistency, overdesign), and ux-microcopy-audit (the icon labels themselves), plus ux-mobile-responsiveness-audit when touch targets matter.
Scope & composition (per docs/orchestration-policy.md §9): this skill owns icon choice, style, and usage. Peers that own a sub-part (defer — each handles its sub-part if reached): ux-buttons owns button label wording and button anatomy. Inherit under a design system (only build from scratch): ux-typography owns the type scale and ux-layout-spacing-grids owns the spacing/grid the icons sit on — take both from the system's tokens when one exists. The full evaluative review defers to the audits above.
Step 0 — Establish context before choosing icons
Ask if not known; state the assumption if proceeding without an answer:
- Platform & library — iOS/macOS lean on SF Symbols; Android on Material symbols; web may use an open set or a custom library. The platform sets default metaphors, rendering, and weights.
- Do icons earn their place here? Icons help with frequent or quick-access actions and scanning. If an icon doesn't simplify the journey, omit it — clutter dilutes the icons that matter. One icon, one action.
- Design-system maturity — a one-off screen needs the right glyphs and labels; a system needs naming, tagging, component structure, and tokens so the set stays consistent and findable.
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.
- 10d ago First seen · 117 lines · 105 tokens per session scan A 11a02f602193
ux-iconography is a skill published in the GitHub repository Uxcel-Lab/product-skills (10 stars, last pushed 2mo ago), licensed MIT. It adds 105 tokens to every session and 2,561 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 2026-08-31.
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