Project-specific prompt optimization knowledge management. Use when storing or retrieving learned patterns from comparisons. Provides schema, extraction criteria, capacity management, and retention scoring.
/plugin marketplace add shinpr/rashomon/plugin install rashomon@rashomonThis skill inherits all available tools. When active, it can use any tool Claude has access to.
{project_root}/.claude/.rashomon/prompt-knowledge.yaml
patterns:
- name: "Pattern name"
what_to_look_for: |
When this pattern applies
improvement: |
How to improve when detected
learned_from: "Date and context"
confidence: 0.0-1.0
times_applied: 0
anti_patterns:
- name: "Anti-pattern name"
what_to_look_for: |
What to avoid
why_bad: |
Why problematic in this project
learned_from: "Date and context"
confidence: 0.0-1.0
metadata:
last_updated: "ISO-8601 timestamp"
total_comparisons: 0
patterns_count: 0
anti_patterns_count: 0
max_entries: 20
ALL conditions must be true:
Confidence Assignment:
| Evidence | Confidence |
|---|---|
| Multiple comparisons confirmed | 0.8+ |
| Single comparison, clear effect | 0.5-0.7 |
| Effect present but uncertain | 0.3-0.5 |
Minimum threshold: 0.3 (entries below this are skipped)
ALL conditions must be true:
Save only entries that are:
Maximum: 20 entries (patterns + anti_patterns combined)
Retention Score: confidence * (1 + log(times_applied + 1))
This formula:
Key Principle: Old entries are valuable. Retention depends on confidence and usage frequency.
Eviction Process:
At start of prompt analysis:
.claude/.rashomon/prompt-knowledge.yaml (if exists)what_to_look_for against current prompttimes_applied for patterns usedAfter comparison (if structural improvement found):
patterns:
- name: "TypeScript interface reference"
what_to_look_for: |
Code generation prompts creating TypeScript types without
referencing existing type definitions in src/types/
improvement: |
Add: "Reference existing types in src/types/ to maintain
consistency and avoid duplicate type definitions"
learned_from: "2026-01-14: Comparison showed better type reuse"
confidence: 0.7
times_applied: 3
When comparison results require knowledge base updates:
Confidence Adjustments:
Entry Management:
This skill should be used when the user asks about libraries, frameworks, API references, or needs code examples. Activates for setup questions, code generation involving libraries, or mentions of specific frameworks like React, Vue, Next.js, Prisma, Supabase, etc.
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.