Design Archivist

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)