Pattern-Learner Skill

Trigger

Asset scores ≥95/100

Process

1. Diff current prompt vs previous attempts
2. Extract language that drove compliance improvement
3. Abstract reusable pattern from specific instance
4. Tag effectiveness (high/medium/low based on first-attempt success)
5. Update /docs/northcote-asset-generation-patterns.md

Example Learning

Input:

• Asset 4 (Wattle + Beetle) scored 96/100 on first attempt
• Previous generic metallic prompts failed (opaque flat paint)
• Success prompt: "Faceted geometric surface with prismatic color shift green→gold→copper"

Extracted Pattern:

## Pattern: Metallic Iridescence (Asset 4, 96/100)

**Context:** Any metallic insect carapace rendering

**Effective Language:**
"Faceted geometric surface" + "prismatic color shift [color1→color2→color3]"

**Why It Works:**
Specifies viewing angle dependence (not flat metallic paint)

**Effectiveness:** HIGH (validated 1st attempt)

**Apply To:**
- Jewel beetles, metallic spiders, iridescent wings

Pattern Structure

## Pattern: [Name] (Asset [N], [Score]/100)

**Context:** [When to use this pattern]

**Effective Language:** [Exact prompt syntax]

**Why It Works:** [Technical explanation]

**Effectiveness:** [HIGH|MEDIUM|LOW]

**Apply To:** [Use cases]

**Avoid:** [Common failure modes]

Integration

Prompt-Composer: Queries pattern library before generation Flash-Sidekick: consult_pro analyzes prompt diffs for pattern extraction Auto-Validator: Scores trigger pattern learning

Self-Improvement Loop

1. Asset validates ≥95 → trigger learning
2. Extract patterns → update library
3. Next asset uses updated patterns
4. Success reinforces pattern (effectiveness++)
5. Failure demotes pattern (effectiveness--)

Database Evolution

Week 1: 5 patterns (from Assets 1-2) Week 2: 12 patterns (from Assets 3-6) Week 4: 25+ patterns (self-reinforcing)

Result: Each new asset easier than previous due to pattern accumulation

Efficiency

Without Learning:

• Asset 10 requires same trial-error as Asset 1
• No institutional knowledge accumulation

With Learning:

• Asset 10 leverages 9 previous successes
• First-attempt success rate increases exponentially

Pattern library evolves with each success. System learns its own best practices.