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Discovers cross-disciplinary connections using structured methods: isomorphic patterns, conceptual bridges, novel applications, and productive tensions. Use for analogies, parallels, or novel insights across fields.
How this skill is triggered — by the user, by Claude, or both
Slash command
/akashicrecords:cross-domain-thinkingThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
A methodological toolkit for discovering and articulating connections across disciplines.
A methodological toolkit for discovering and articulating connections across disciplines.
Identify structural similarities that transcend domain boundaries.
Process:
Examples:
Output format:
"The structure here is [abstract pattern]. This same structure appears in [Domain B] as [concrete manifestation]. What this reveals: [insight about the deeper principle]."
Use a principle from one field to illuminate another.
Process:
Examples:
Output format:
"In [Domain A], [concept] works by [mechanism]. Applying this lens to [Domain B]: [new interpretation]. This suggests [actionable insight or prediction]."
Transfer solutions or techniques across contexts.
Process:
Caution flags:
Output format:
"[Domain A] solved [problem] using [approach]. [Domain B] faces analogous challenge: [description]. Potential transfer: [adapted solution]. Transfer risk: [what might not hold]."
Find where different frameworks conflict instructively.
Process:
Examples:
Output format:
"[Framework A] says [X]. [Framework B] says [Y]. The tension: [specific conflict]. What A captures that B misses: [insight]. What B captures that A misses: [insight]. Resolution path: [synthesis or scope conditions]."
Analyze user request:
Select mode:
"How does X relate to Y?" -> Isomorphic Patterns or Conceptual Bridges
"Can we apply X to solve Y?" -> Novel Applications
"X says one thing, Y says another" -> Productive Tensions
"Find connections to X" -> Start with Isomorphic Patterns
For Isomorphic Patterns:
For Conceptual Bridges:
For Novel Applications:
For Productive Tensions:
Abstraction Ladder:
Epistemic Marking:
After generating cross-domain insights, consider:
Example integration:
User: "How does natural selection relate to algorithm design?"
Skill workflow:
1. Identifies Conceptual Bridge mode
2. Analyzes natural selection mechanisms
3. Maps to evolutionary algorithms
4. Presents insights with epistemic marking
Optional follow-up:
"Would you like me to save these insights to your knowledge base?"
-> Invokes add-content to capture for future reference
User: "I'm noticing that both social media viral content and disease outbreaks seem to spread similarly. What's the connection?"
Skill response:
The structure here is network propagation with threshold dynamics. In both cases:
- Transmission occurs through connected nodes (people)
- Each transmission has a probability of success
- Critical mass triggers exponential growth
- Network topology determines spread patterns
This same structure appears in:
- Neural activation cascades in the brain
- Bank run panics in financial systems
- Idea adoption in scientific communities
What this reveals: The mathematics of contagion is substrate-independent. Understanding one gives you tools for all. The key variables are: connection density, transmission probability, and recovery/immunity rate.
User: "Engineering uses 'margin of safety' - could that concept help with personal finance decisions?"
Skill response:
Engineering solved the problem of uncertainty in material properties using margin of safety: design for 2-3x expected load to handle unknowns.
Personal finance faces an analogous challenge: income volatility, unexpected expenses, lifestyle inflation.
Potential transfer:
- Instead of spending up to your income limit, maintain a 2x margin
- Emergency fund = "factor of safety" for income disruption
- Budget for 50% of actual income = structural margin for unknowns
Transfer risk: Unlike engineering where failure modes are understood, life has "black swan" events. Engineering margins are calculated; financial margins are estimated. The principle transfers, but calibration requires different methods.
User: "Economists say people are rational actors, but psychologists show we're full of biases. Who's right?"
Skill response:
Rational actor model says: People optimize utility given constraints and information.
Behavioral psychology says: People use heuristics that systematically deviate from optimization.
The tension: Both can't be fully true. If we're rational optimizers, biases shouldn't persist. If we're bias-driven, markets shouldn't work as well as they do.
What rational models capture that behavioral misses: Aggregate market behavior often looks rational even when individuals aren't. Markets select for rational-ish outcomes.
What behavioral captures that rational misses: Individual decision-making, especially under uncertainty or emotional load. Where arbitrage is difficult.
Resolution path: Bounded rationality - people are rational within cognitive constraints. Rational at the margin, biased at the baseline. Different scopes of application, not contradiction.
npx claudepluginhub legacybridge-tech/claude-plugins --plugin akashicrecordsRoutes analogical reasoning to the right sub-skill: boundary-testing, domain-transfer, perspective-shifting, or structure-mapping. Use for finding comparisons, importing solutions, or testing analogies.
Synthesizes information from multiple sources into coherent insights and applies analogical reasoning to transfer knowledge across domains. Useful for literature reviews, stakeholder feedback, and creative problem-solving.
Facilitates analogical transfer sessions: abstracts problem structure, maps to distant domains like biology or history, transfers operating principles. Supports --brief, --tetralemma, --polarity modes for creative problem-solving.