skills/naturalistic-insight/SKILL.md
Research on how insights and creative solutions emerge naturally during problem-solving and expertise
npx skillsauth add curiositech/windags-skills naturalistic-insightInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Load this skill when the user faces challenges where reframing rather than optimizing is needed:
Primary Decision Matrix: Anomaly Type × Context → Pathway Selection
IF anomalous data persists despite explanation attempts:
├─ IF in research/investigation context → Contradiction Pathway
│ └─ Action: Treat anomaly as most reliable data point
│ └─ Question: "What frame makes this the normal case?"
├─ IF in operational context with time pressure → Knowledge Shield Check
│ └─ Action: Document anomaly for later analysis
│ └─ Escalate to subject matter experts
└─ IF in learning/exploration context → Pattern Accumulation
└─ Action: Log as gradual insight opportunity
└─ Set up tracking infrastructure
IF experiencing genuine impasse (multiple solution attempts failed):
├─ IF problem is well-defined domain → Execution Problem
│ └─ Action: Standard decomposition and optimization
├─ IF problem definition feels wrong → Desperation Pathway
│ └─ Action: Question foundational assumptions
│ └─ Replace strongest anchors systematically
└─ IF expertise feels like obstacle → Expertise Paradox
└─ Action: Leverage knowledge for pattern detection
└─ Remain open to frame revision
IF noticing unexpected connections across cases:
├─ IF connection is metaphorical → Connection Pathway
│ └─ Action: Add bridging anchor to mental model
├─ IF connection reveals causal relationship → Analytical Extension
│ └─ Action: Standard hypothesis testing
└─ IF connection spans domains → Cross-Domain Transfer
└─ Action: Map structural similarities
IF designing for insight generation:
├─ IF users are domain experts → Expertise-Enabled Design
│ └─ Provide pattern libraries and anomaly detection
├─ IF organizational context → Assess Error vs. Insight Culture
│ └─ IF error-focused: Create protected spaces
│ └─ IF insight-friendly: Integrate with existing processes
└─ IF AI/agent system → Multi-Pathway Architecture
└─ Build contradiction, connection, and desperation modules
1. Rubber Stamp Anomaly Dismissal
2. Sudden Insight Fixation
3. Expertise Contamination Fear
4. Execution Task Decomposition
5. Innovation Theater Deployment
Context: 1981, CDC epidemiologist reviewing unusual pneumonia cases in gay men.
Initial Frame: Isolated outbreak, likely lifestyle-related immune suppression.
Anomaly: Hemophiliac patients presenting identical symptoms despite completely different demographics.
Novice Response: "Hemophiliacs have compromised health anyway—probably coincidence."
Expert Application of Skill:
Outcome: Discovery of bloodborne transmission route, saving thousands of lives.
Decision Points Navigated:
Context: Fire commander Klein interviewed, routine house fire response.
Initial Frame: Standard interior attack, crew positioned normally.
Impasse Signals: Fire not responding to water, heat increasing unexpectedly, no visible progress.
Expert Application of Skill:
Outcome: Crew evacuated 30 seconds before floor collapsed.
Decision Points Navigated:
Context: Darwin studying coral formations during Beagle voyage.
Pattern Accumulation: Observing multiple atolls across different locations over months.
Connection Emergence: Noticing structural similarity between atolls and barrier reefs around volcanic islands.
Expert Application of Skill:
Outcome: Revolutionary theory of coral formation, confirmed by drilling decades later.
Decision Points Navigated:
Frame Coherence Check:
[ ] New frame explains previously unexplained anomalies without special pleading
[ ] Frame generates testable predictions different from old model
[ ] Revised understanding integrates smoothly with established domain knowledge
[ ] Frame addresses root cause, not just symptoms
Prediction Power Validation: [ ] New frame successfully predicts behavior in untested cases [ ] Predictions are specific enough to risk falsification [ ] Frame explains both positive and negative cases in dataset [ ] Model performs better than previous best explanation
Expert Acceptance Assessment:
[ ] Domain experts can follow the reasoning path
[ ] Insight leverages rather than dismisses existing expertise
[ ] Other experts can replicate the insight given same data
[ ] Resistance based on evidence, not just unfamiliarity
Anomaly Resolution Verification: [ ] Original contradiction/impasse is genuinely resolved, not just deferred [ ] Resolution doesn't create larger contradictions elsewhere [ ] Previously dismissed data now makes sense within new frame [ ] Weak anchors that triggered insight are now integrated
Implementation Readiness: [ ] Clear next actions follow from the insight [ ] Resource and timeline implications are understood [ ] Organizational barriers to implementation are identified [ ] Success metrics for new approach are defined
This skill is NOT for:
systematic-optimization insteaddebugging-protocols insteadcontinuous-improvement insteadtask-decomposition insteadcrisis-response insteadDelegate to other skills when:
creative-ideation insteadsystematic-inventive-thinking insteadbehavior-change-design insteaddecision-analysis insteadgroup-problem-solving insteadCritical boundary: This skill focuses on naturalistic insight (how insights actually emerge in real contexts) not laboratory creativity (puzzle-solving, divergent thinking exercises). If the user wants "innovation training" or "creative thinking workshops," redirect to appropriate facilitation skills.
data-ai
license: Apache-2.0 NOT for unrelated tasks outside this domain.
development
Use when designing caching strategies (cache-aside, write-through, write-behind), implementing distributed locks, building rate limiters, leaderboards, real-time streams (XADD/consumer groups), pub/sub, or tuning eviction policies. Triggers: thundering-herd on cache miss, dogpile on key expiry, Redlock vs SET-NX-PX choice, sliding-window rate limiter, hot-key on a single cluster slot, big-key blowup, MULTI/EXEC across slots, KEYS in production. NOT for Redis Cluster operations/admin (different domain), embedded KV (SQLite, leveldb), in-process LRU caches, or Memcached.
tools
Drawing the `'use client'` boundary correctly in React Server Components apps (Next.js App Router, RSC frameworks) — leaf-pushing, slot composition, serialization rules, and environment poisoning prevention. Grounded in react.dev and Next.js 16 docs.
development
Use when designing rate limiting for an API, choosing between token bucket / sliding window / leaky bucket / fixed window, implementing it in Redis, deciding edge (Cloudflare/Upstash) vs origin enforcement, sizing per-user vs per-IP vs per-endpoint quotas, returning the right 429 response with Retry-After, or fixing the boundary-burst bug in fixed-window limiters. Triggers: 429 too many requests, INCR + EXPIRE, ZADD + ZREMRANGEBYSCORE + ZCARD, X-RateLimit-Remaining header, Cloudflare WAF rate limiting rules, Upstash @upstash/ratelimit, leaky bucket shaping vs policing, distributed rate limiter consistency. NOT for DDoS mitigation specifically (different scale), CAPTCHA / bot management, full WAF design, or per-user quota billing.