frontend-design-intelligence

A design-planning guide for web interfaces that turns an unclear product or page idea into a short brief about the audience, page pattern, visual style, density, and domain-specific risks.

In plain words
What is it for?
Use it before designing a landing page, dashboard, or other interface when you need to choose a structure, visual direction, motion, or information density.
Why use it?
It helps prevent generic layouts and unsuitable design choices when the product, users, or page purpose are not fully defined.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/ytvee-dev/webdev-agent-kit/frontend-design-intelligence
Any agent
npx skills add ytvee-dev/webdev-agent-kit --skill frontend-design-intelligence
Clone the repo
git clone --depth 1 https://github.com/ytvee-dev/webdev-agent-kit

Made for: Claude Code, Codex.

Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,055 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00045 $0.01055
Opus 5 $0.00023 $0.00528
Sonnet 5 $0.00009 $0.00211
Haiku 4.5 $0.00005 $0.00105

Measured 2d ago against content hash e9072953fb9f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

frontend-design-intelligence 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 2d 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.

skills/frontend-design-intelligence/SKILL.md · 127 lines

How it starts

The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Frontend Design Intelligence

Purpose

Create a compact design intelligence brief before visual direction when a UI task needs product-category grounding, page-pattern choice, density decisions, or domain-specific anti-pattern checks.

This skill adapts design-system reasoning into the WebDev Agent Kit model without becoming a UI framework, CLI generator, or package installer.

When To Use

Use after prompt intent routing when the task is Standard Workflow or Deep Workflow and one or more are true:

  • product type, page type, audience, or user job is vague;
  • the user asks for visual style, landing structure, dashboard structure, or distinctive UI direction;
  • the page needs visual variance, motion, or density decisions;
  • frontend-design-director needs better grounding before writing a Design Direction Contract.

When Not To Use

Do not use for Fast Lookup, tiny edits, purely technical bugfixes, code implementation, live Figma inspection, package installation, or new styling systems.

Required Context

  1. Read AGENTS.md.
  2. Read common/prompt-intent-routing-rules.md when workflow level is unclear.
  3. Read relevant project overlays when present.
  4. Read only relevant references from this skill:
    • references/product-pattern-matrix.md;
    • references/design-dials.md;
    • references/product-anti-patterns.md.
  5. Read supplied screenshots, briefs, inspect notes, or existing route files only when they materially affect the brief.

Tool Contract

  • May read project overlays and relevant source files.
  • Must not run design generators or external CLIs.
  • Must not create or edit app source code.
  • Must not create a global design system unless explicitly requested, and then only inside .agents/project/**.
  • Must not use Figma MCP.

Workflow

  1. Identify product category, audience, page type, and single job.
  2. If required facts are missing, infer the smallest useful assumption and label it.
  3. Select a likely page pattern from the user job, not from a generic style catalog.
  4. Set design dials: visual variance, motion intensity, and information density.
  5. Identify domain UX risks.
  6. Identify product-specific anti-patterns and generic template risks.
  7. Produce a compact Design Intelligence Brief.
  8. Hand off to frontend-design-director when visual direction is needed.

Read the full file on GitHub · 127 lines

Files

What ships with it

4 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. 2d ago First seen · 127 lines · 45 tokens per session scan A e9072953fb9f

Subscribe to this mod's changes

frontend-design-intelligence is a skill published in the GitHub repository ytvee-dev/webdev-agent-kit (5 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 45 tokens to every session and 1,055 once invoked, about $0.0002 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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