design-archivist

Q: How do I install design-archivist?

Run npx skills add https://github.com/curiositech/some_claude_skills --skill design-archivist in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/design-archivist/ (personal) or .claude/skills/design-archivist/ (project).

Q: Which AI agents can use design-archivist?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Q: Is design-archivist safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Q: Who maintains design-archivist?

It is published by curiositech in curiositech/some_claude_skills. It has 321 recorded installs.

by curiositechFrontend & Design

Long-running design anthropologist that builds comprehensive visual databases from 500-1000 real-world examples, extracting color palettes, typography patterns, layout systems, and interaction design across any domain (portfolios, e-commerce, SaaS, adult content, technical showcases). This skill should be used when users need exhaustive design research, pattern recognition across large example sets, or systematic visual analysis for competitive positioning.

Installs: 321
Last 24h: —
Trending rank: —
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/curiositech/some_claude_skills --skill design-archivist

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads design-archivist automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Design Archivist

A design anthropologist that systematically builds visual databases through large-scale analysis of real-world examples. This is a long-running skill designed for multi-day research (2-7 days for 500-1000 examples).

Quick Start

User: "Research design patterns for fintech apps targeting Gen Z"

Archivist:
1. Define scope: "fintech landing pages, Gen Z audience (18-27)"
2. Set target: 500 examples over 2-3 days
3. Identify seeds: Venmo, Cash App, Robinhood, plus competitors
4. Begin systematic crawl with checkpoints every 10 examples
5. After 48 hours: Deliver pattern database with:
   - Color trends
   - Typography patterns
   - Layout systems
   - White space opportunities

When to Use

Use for:

Exhaustive design research (300-1000 examples)
Pattern recognition across large example sets
Competitive visual analysis
Trend identification with data backing
Domain-specific design language extraction

NOT for:

Quick design inspiration (use Dribbble/Awwwards directly)
Single example analysis
Small samples (<50 examples)
Real-time trend spotting (this takes days)

Core Process

1. Domain Initialization

Define target domain and audience
Set target count (300-1000 based on specificity)
Identify seed URLs or search queries
Establish focus areas

2. Systematic Crawling

For each example:

Capture visual snapshot
Record metadata (URL, timestamp, context)
Extract Visual DNA (colors, typography, layout, interactions)
Analyze contextual signals (audience, positioning, success indicators)
Apply categorical tags
Save checkpoint every 10 examples

3. Pattern Extraction

After accumulating examples, identify:

Dominant patterns - The "norm" (most common approaches)
Emerging patterns - The "future" (gaining traction)
Deprecated patterns - The "past" (avoid these)
Outlier patterns - The "experimental" (unique approaches)

Visual DNA Extraction

For each example, extract:

Category	What to Extract
Colors	Palette, primary/secondary/accent, dominance percentages
Typography	Font families, weights, sizes, hierarchy
Layout	Grid system, spacing base, structure, whitespace
Interactions	Hover effects, transitions, scroll behaviors
Animation	Presence level, types, timing

See references/data_structures.md for full TypeScript interfaces.

Domain Quick Reference

Domain	Focus Areas	Seed Sources
Portfolios	Clarity, credibility, storytelling	Awwwards, Dribbble, Behance
SaaS Landing	Conversion, trust signals, pricing	Product Hunt, SaaS directories
E-Commerce	Product photos, checkout, mobile	Shopify stores, major retailers
Adult Content	Premium positioning, discretion	Adult ad networks, VR platforms
Technical Demos	Visual drama, performance, interactivity	Shadertoy, Codrops, ArtStation

See references/domain_guides.md for detailed domain strategies.

Long-Running Infrastructure

Checkpointing Strategy

Save checkpoint every 10 examples
Include job ID, progress count, queue state, timestamp
Keep last 3 checkpoints as backup

Progress Reporting

Report at intervals:

"Analyzed 250/1000 examples (25% complete)"
"Current rate: 100 examples/day"
"Estimated completion: 7 days"
"Top emerging pattern: glassmorphic cards (15% of recent examples)"

Rate Limiting

Max 1 request per second per domain
Respect robots.txt
Implement exponential backoff on errors

Anti-Patterns

1. Scraping Too Aggressively

Symptom: Requests every 100ms, same domain hammered repeatedly Fix: 1 request/second max, respect robots.txt, exponential backoff

2. No Checkpointing

Symptom: Running 24 hours straight without saving Fix: Save every 10 examples with timestamp and queue state

3. Ignoring Domain Context

Symptom: Applying e-commerce patterns to portfolio sites Fix: Research domain-specific best practices first

4. Analysis Paralysis

Symptom: 30 minutes per example across 1000 examples Fix: Batch process in groups of 10, deep-dive only on outliers

5. Insufficient Diversity

Symptom: Only analyzing top-tier examples Fix: Include leaders, mid-tier, and independents; geographic diversity

6. Ignoring Historical Context

Symptom: Treating all patterns as current Fix: Use Wayback Machine, note when patterns emerged, track evolution

Output Format

Generate comprehensive research packages with:

Meta: Domain, count, date range, depth
Examples: Full visual database
Patterns: Dominant, emerging, deprecated, outlier
Insights: Color/typography/layout/interaction trends
Recommendations: Safe choices, differentiators, patterns to avoid

Cost and Scale

For 1000-example analysis:

Item	Cost
Screenshots	~$20 (Playwright cloud @ $0.02/each)
LLM Analysis	~$15 (100 batches × $0.15)
Storage	~$0.01 (200MB)
Total	~$35
Runtime	48-72 hours

Inform users of scope and cost before beginning.

Reference Files

File	Contents
`references/data_structures.md`	TypeScript interfaces for VisualDNA, ContextAnalysis, Checkpoint
`references/domain_guides.md`	Detailed domain-specific strategies and focus areas

Covers: Design Research | Pattern Recognition | Visual Analysis | Competitive Intelligence

Use with: web-design-expert (apply findings) | competitive-cartographer (market context)

FAQ

What does the design-archivist skill do?

How do I install design-archivist?

Run npx skills add https://github.com/curiositech/some_claude_skills --skill design-archivist in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/design-archivist/ (personal) or .claude/skills/design-archivist/ (project).

Which AI agents can use design-archivist?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is design-archivist safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains design-archivist?

It is published by curiositech in curiositech/some_claude_skills. It has 321 recorded installs.