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 IgniteUI/igniteui-cli --skill igniteui-wc-generate-from-image-designgit clone --depth 1 https://github.com/IgniteUI/igniteui-cliWrote 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/igniteui/igniteui-cli/igniteui-wc-generate-from-image-design)<a href="https://agentmods.dev/skills/igniteui/igniteui-cli/igniteui-wc-generate-from-image-design"><img src="https://agentmods.dev/badge/skills/igniteui/igniteui-cli/igniteui-wc-generate-from-image-design/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/igniteui/igniteui-cli/igniteui-wc-generate-from-image-design"><img src="https://agentmods.dev/badge/skills/igniteui/igniteui-cli/igniteui-wc-generate-from-image-design.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 | $0.00121 | $0.03751 |
| Opus 5 | $0.00060 | $0.01876 |
| Sonnet 5 | $0.00024 | $0.00750 |
| Haiku 4.5 | $0.00012 | $0.00375 |
Grade A, and why
igniteui-wc-generate-from-image-design 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 — 229 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implementing Ignite UI Web Components Views from Design Images
MANDATORY AGENT PROTOCOL
Before writing any implementation code, you must complete these steps in order:
- Analyze the image and identify all visible regions and UI patterns.
- Read references/component-mapping.md and references/gotchas.md.
- This skill is Web Components-first. Check package layout or licensing only when package choice, component registration, or theming depend on it.
- To apply a theme, use the theming workflow from this skill and the dedicated
igniteui-wc-customize-component-themeskill; use theigniteui-themingMCP tools instead of styling from memory. - Call
get_docfor every chosen component family before using it. - Only then start coding.
Workflow
- Analyze the design image - Read the image, identify every UI section, component, layout structure.
- Confirm package layout if needed - Web Components packages are split by component family; check package layout or licensing only when package choice, component registration, or theming depend on it.
- Discover components - Call
list_componentswith targeted filters to find matching components for each UI pattern. - Look up component docs - Call
get_docfor every chosen component family before coding. - Generate theme - (a) To generate a theme, first extract colors and create a color palette using
create_paletteorcreate_custom_palettedepending on the scenario. Then extract elevations and callcreate_elevations. Then extract typography and callcreate_typography. Then callcreate_themewhen Sass is configured, or import the closest pre-built theme CSS. (b) After a theme exists, prefer using design tokens or scoped semantic CSS variables over raw literals. (c) For every Ignite UI component family that exposes design tokens, callget_component_design_tokens, map extracted image tokens to token roles, then callcreate_component_themewith the tokens differing from the global theme for the specific component. - Implement - Build the screenshot-first layout, data, and view components.
- Refine - Use the
set_size,set_spacing,set_roundnesstools to refine the view's visual fidelity against the image, then iterate on implementation and theming until the view matches the design closely. - Validate - Build, test, run, compare against the image, and fix differences.
What ships with it
2 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 · 229 lines · 121 tokens per session scan A a1ab958485f3
igniteui-wc-generate-from-image-design is a skill published in the GitHub repository IgniteUI/igniteui-cli (136 stars, last pushed today), licensed MIT. It adds 121 tokens to every session and 3,751 once invoked, about $0.0006 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.
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