ranbot-ai Idea Darwin Engine
A round-based idea iteration system that treats ideas as competing organisms — scoring, selecting, crossing, and evolving them through structured rounds to surface the strongest concepts.
Overview
Most idea management tools are filing cabinets: they store ideas, tag them, and let them rot. Idea Darwin flips the paradigm — instead of organizing ideas, it lets them compete. Every idea is a living species on an evolution island. Each round, the fittest get deepened, different ideas cross-pollinate to produce unexpected hybrids, and external stimuli trigger mutations.
When to Use This Skill
- Use when you have many scattered ideas and need to systematically evaluate and develop them
- Use when you want to discover unexpected connections between ideas from different domains
- Use when you need structured iteration rather than one-shot brainstorming
- Use when you want a scoring framework to prioritize which ideas deserve more investment
Core Concepts
Evolution Island Metaphor
Your ideas are alive on this island. Like organisms, they follow three core laws:
- Evolution — Each round, the system deepens the most viable ideas through structured research: filling logical gaps, clarifying paths, identifying risks.
- Crossbreeding — The system cross-pollinates different ideas. A technical approach from work meets an observation from daily life, producing directions you never imagined.
- Mutation — External stimuli (industry news, theories, conversations) trigger mutations, spawning entirely new species.
Species Cards
Every idea gets a structured card recording: core question, full description, lineage (parent/child IDs), 6-dimensional scores, and change history.
6-Dimensional Scoring
| Dimension | Weight | What It Measures |
|---|---|---|
| Novelty | 10% | Genuine breakthrough or repetition? |
| Feasibility | 20% | Technically and resource-wise achievable? |
| Value | 20% | Impact if successful? |
| Logic | 20% | Internally consistent, no gaps? |
| Cross Potential | 10% | Can spark something new when combined? |
| Verifiability | 20% | Can we design a validation path? |
Idea Lifecycle
seed → exploring → refining → crossing → validated → dormant
The user always has final say on all life-or-death decisions. The system only recommends.
Step-by-Step Guide
1. Write Your Ideas
Create an ideas.md file:
## Personal knowledge base that learns my style
I want a system that reads everything I write and gradually learns how I think.
## Commute-to-podcast converter
Record voice memos during my commute, auto-convert them into podcast scripts.
2. Initialize Your Island
/idea-darwin init
3. Start Evolving
/idea-darwin round
4. Keep Feeding the Island
Append new ideas to ideas.md, add environmental variables to stimuli.md.
Examples
Example 1: Initialize
/idea-darwin init --budget 8 --actions 3
Example 2: Run Multiple Rounds
/idea-darwin round 3
Example 3: Manage Ideas
/idea-darwin dormant IDEA-0005
/idea-darwin wake IDEA-0005
Best Practices
- Do: Write ideas as rough as you want — the system structures them
- Do: Add external stimuli to prevent idea convergence
- Do: Run disruption rounds to surface overlooked ideas
- Don't: Over-curate initial ideas — let evolution filter
- Don't: Ignore the "Decisions Needed" section in briefings
Additional Resources
- GitHub Repository
- Available in 3 languages: English, Chinese, Japanese
- ClawHub:
clawhub install idea-darwin
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.