igniteui-blazor-generate-from-image-design

igniteui-blazor-generate-from-image-design is a skill for Claude Code from IgniteUI/igniteui-cli. It costs 127 tokens per session (4,427 once invoked), scanned A, original, MIT.

A guide for building Blazor screens from design images using Ignite UI components, which are ready-made interface elements for .NET web apps. It covers turning a screenshot, mockup, or wireframe into a working view.

In plain words
What is it for?
Use it to implement Blazor views from images, choose matching Ignite UI components, check their documentation, and apply an appropriate theme.
Why use it?
It helps connect what is visible in a design to suitable components, documentation, and styling steps. This reduces guesswork when recreating a design in Blazor.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter.

Good fit Use it to implement Blazor views from images, choose matching Ignite UI components, check their documentation, and apply an appropriate theme.

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Install with agentmods
npx agentmods add skills/igniteui/igniteui-cli/igniteui-blazor-generate-from-image-design
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.

Any agent
npx skills add IgniteUI/igniteui-cli --skill igniteui-blazor-generate-from-image-design
Clone the repo
git clone --depth 1 https://github.com/IgniteUI/igniteui-cli

Made for: Claude Code.

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 igniteui-blazor-generate-from-image-design

README.md
[![agentmods](https://agentmods.dev/badge/skills/igniteui/igniteui-cli/igniteui-blazor-generate-from-image-design.svg)](https://agentmods.dev/skills/igniteui/igniteui-cli/igniteui-blazor-generate-from-image-design)
Your own site
<a href="https://agentmods.dev/skills/igniteui/igniteui-cli/igniteui-blazor-generate-from-image-design"><img src="https://agentmods.dev/badge/skills/igniteui/igniteui-cli/igniteui-blazor-generate-from-image-design.svg" alt="Measured on agentmods" height="20"></a>
Per session 127 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,427 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00127 $0.04427
Opus 5 $0.00063 $0.02214
Sonnet 5 $0.00025 $0.00885
Haiku 4.5 $0.00013 $0.00443

Measured 7d ago against content hash d60678a1b801, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

igniteui-blazor-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 7d 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.

packages/cli/templates/blazor/igb/projects/ai-config/files/skills/igniteui-blazor-generate-from-image-design/SKILL.md · 285 lines

How it starts

The opening of the file, as written. The whole thing — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Implementing Ignite UI Blazor Views from Design Images

MANDATORY AGENT PROTOCOL

Before writing any implementation code, you must complete these steps in order:

  1. Analyze the image and identify all visible regions and UI patterns.
  2. Read references/component-mapping.md.
  3. This skill is Blazor-only. Check NuGet package (IgniteUI.Blazor.Lite, IgniteUI.Blazor.GridLite for general purpose components and light-weight grid, or IgniteUI.Blazor / IgniteUI.Blazor.Trial for specialized feature-rich grids and charts) only when theming or component availability depends on it.
  4. To apply a theme, use the theming workflow from this skill and the dedicated igniteui-blazor-theming skill; use the igniteui-theming MCP tools instead of styling from memory.
  5. Call get_doc for every chosen component family before using it.
  6. Read references/gotchas.md now — after docs, before writing any code. Read the file in full. Some entries are component-specific; others apply broadly to any chart, any themed component, or any scoped CSS. Apply every entry that is relevant to what you are building. This is a blocking step: do not start implementation until you have read the whole file and checked it against your component list.
  7. Only then start coding.

Workflow

  1. Analyze the design image - Read the image, identify every UI section, component, layout structure.
  2. Confirm NuGet package if needed - this skill is Blazor-only; use IgniteUI.Blazor.Lite, IgniteUI.Blazor.GridLite for general purpose components and the light-weight grid, and IgniteUI.Blazor (trial version available publicly as IgniteUI.Blazor.Trial) for specialized feature-rich grids and charts.
  3. Discover components - Call list_components with targeted filters and framework: "blazor" to find matching components for each UI pattern.
  4. Look up component docs - Call get_doc for every chosen component family before coding.
  5. Generate theme - (a) Extract colors and call create_palette or create_custom_palette with platform: "blazor" and output: "css" — do not use create_theme for Blazor, it produces Sass requiring compilation. Optionally call create_elevations and create_typography for elevation and font overrides. (b) After a palette exists, prefer using design tokens or scoped semantic CSS variables over raw literals. (c) For every Ignite UI component, call get_component_design_tokens, map extracted image tokens to token roles, then call create_component_theme with the tokens differing from the global theme for the specific component.
  6. Implement - Build the screenshot-first layout, data, and view components.
  7. Refine - Use the set_size, set_spacing, set_roundness tools to refine the view's visual fidelity against the image, then iterate on implementation and theming until the view matches the design closely.
  8. Validate - Build, test, run, compare against the image, and fix differences.

Read the full file on GitHub · 285 lines

Files

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.

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. 7d ago First seen · 285 lines · 127 tokens per session scan A d60678a1b801

Subscribe to this mod's changes

igniteui-blazor-generate-from-image-design is a skill published in the GitHub repository IgniteUI/igniteui-cli (136 stars, last pushed 3d ago), licensed MIT. It adds 127 tokens to every session and 4,427 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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