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.
git clone --depth 1 https://github.com/catlog22/Claude-Code-WorkflowWrote 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/commands/catlog22/claude-code-workflow/layout-extract)<a href="https://agentmods.dev/commands/catlog22/claude-code-workflow/layout-extract"><img src="https://agentmods.dev/badge/commands/catlog22/claude-code-workflow/layout-extract/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/commands/catlog22/claude-code-workflow/layout-extract"><img src="https://agentmods.dev/badge/commands/catlog22/claude-code-workflow/layout-extract.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 | $0.00000 | $0.06806 |
| Opus 5.5 | $0.00000 | $0.02722 |
| Sonnet 5.5 | $0.00000 | $0.01361 |
| Haiku 4.5 | $0.00000 | $0.00681 |
Grade A, and why
layout-extract 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 1mo 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 — 793 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Auto Mode
When --yes or -y: Skip all clarification questions, use AI-inferred layout decisions.
Layout Extraction Command
Overview
Extract structural layout information from reference images or text prompts using AI analysis. Supports two modes:
- Exploration Mode (default): Generate multiple contrasting layout variants
- Refinement Mode (
--refine): Refine a single existing layout through detailed adjustments
This command separates the "scaffolding" (HTML structure and CSS layout) from the "paint" (visual tokens handled by style-extract).
Strategy: AI-Driven Structural Analysis
- Agent-Powered: Uses
ui-design-agentfor deep structural analysis - Dual Mode: Exploration (multiple contrasting variants) or Refinement (single layout fine-tuning)
- Output:
layout-templates.jsonwith DOM structure, component hierarchy, and CSS layout rules - Device-Aware: Optimized for specific device types (desktop, mobile, tablet, responsive)
- Token-Based: CSS uses
var()placeholders for spacing and breakpoints
Execution Process
Input Parsing:
├─ Parse flags: --design-id, --session, --images, --prompt, --targets, --variants, --device-type, --interactive, --refine
└─ Decision (mode detection):
├─ --refine flag → Refinement Mode (variants_count = 1)
└─ No --refine → Exploration Mode (variants_count = --variants OR 3)
Phase 0: Setup & Input Validation
├─ Step 1: Detect input, mode & targets
├─ Step 2: Load inputs & create directories
└─ Step 3: Memory check (skip if cached)
Phase 1: Layout Concept/Refinement Options Generation
├─ Step 0.5: Load existing layout (Refinement Mode only)
├─ Step 1: Generate options (Agent Task 1)
│ └─ Decision:
│ ├─ Exploration Mode → Generate contrasting layout concepts
│ └─ Refinement Mode → Generate refinement options
└─ Step 2: Verify options file created
Phase 1.5: User Confirmation (Optional)
└─ Decision (--interactive flag):
├─ --interactive present → Present options, capture selection
└─ No --interactive → Skip to Phase 2
Phase 2: Layout Template Generation
├─ Step 1: Load user selections or default to all
├─ Step 2: Launch parallel agent tasks
└─ Step 3: Verify output files
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.
- 1mo ago First seen · 793 lines · 0 tokens per session scan A 6285d3a9c152
layout-extract is a command published in the GitHub repository catlog22/Claude-Code-Workflow (2,125 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 6,806 tokens. 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 commands, from other repositories
multi-frontend
Run a frontend-focused multi-model workflow for components, layouts, animation, and UI polish.
gan-design
Run a generator/evaluator design loop for frontend or visual work with bounded iterations and scoring.
svelte:storybook
General-purpose Storybook assistance for SvelteKit projects, including setup guidance, best practices, and common tasks.
design-system
Command "design-system" from XINGANLIU/design-system-generator-skill, covering design system generator — claude code command, usage: /design-system [font-family] [style] and example: /design-system #6366f1 "outfit" rounded.
ux-recommend
The v2 flagship. Runs the 5-parallel-search Python engine across 11 data manifests (75+ styles, 170+ palettes, 65+ type pairs, 120+ components, 170+ industries, 110+ UX laws, 50+ motion presets, 120+ anti-patterns, 92 brand specs) and returns a complete recommended design system for your project — with always-on…
extract
Pull repeated patterns into reusable components and design tokens.