Self Improving Cognition
by @harrylabsj
Systematic improvement of thinking patterns, decision quality, problem-solving abilities, and mental performance. Use when noticing cognitive biases, making...
clawhub install self-improving-cognitionπ About This Skill
name: self-improving-cognition description: "Systematic improvement of thinking patterns, decision quality, problem-solving abilities, and mental performance. Use when noticing cognitive biases, making important decisions, solving complex problems, or wanting to enhance mental clarity and effectiveness."
Self-Improving Cognition
Structured approach to cognitive enhancement through measurable tracking of thinking patterns, bias identification, decision analysis, and mental skill development. Transforms vague "think better" into specific, improvable cognitive competencies.
Quick Reference
| Situation | Action | |-----------|--------| | Making important decision | Log decision context, alternatives, reasoning, track outcome | | Noticing cognitive bias | Identify bias type, record instance, develop correction strategy | | Solving complex problem | Document problem space, approaches tried, breakthrough insights | | Feeling mentally foggy | Track mental clarity factors, identify patterns, adjust routines | | Learning new complex concept | Map understanding, identify gaps, track mastery progression |
Cognitive Dimensions & Metrics
Attention & Focus (Cognitive Control)
Memory & Recall (Information Processing)
Logical Reasoning (Analytical Thinking)
Creative Thinking (Generative Cognition)
Metacognition (Thinking About Thinking)
Logging Format
Cognitive Assessment Baseline
Append to.learnings/cognition/BASELINE.md:## [COG-YYYYMMDD-001] Cognitive Baseline AssessmentAssessed: 2026-03-12T10:00:00Z
Overall Cognitive Fitness: 6.8/10
Strengths: Logical reasoning, Metacognition
Areas for Improvement: Sustained attention, Creative fluency
Dimension Scores (1-10)
1. Attention & Focus: 5.5/10
- Sustained: 25 minutes average
- Selective: 6/10 (easily distracted by notifications)
- Recovery: 3 minutes after interruption
2. Memory & Recall: 6.0/10
- Working: 5Β±2 items (digit span)
- Long-term: 7/10 (good factual recall)
- Speed: 2.3 seconds average retrieval
3. Logical Reasoning: 8.0/10
- Deductive: 85% accuracy
- Inductive: 8/10 (strong pattern recognition)
- Fallacy Detection: 75% accuracy
4. Creative Thinking: 5.0/10
- Fluency: 12 ideas/10 minutes
- Originality: 4/10 (mostly conventional)
- Connections: 3 unusual associations/ session
5. Metacognition: 7.5/10
- Accuracy: 80% (self-assessment vs. performance)
- Strategy Awareness: 8/10 (knows thinking processes)
- Error Detection: 7/10 (catches 70% of own errors)Cognitive Bias Inventory
Confirmation Bias: Moderate (seeks confirming evidence)
Anchoring: High (influenced by initial information)
Availability Heuristic: Moderate (overweights recent examples)
Planning Fallacy: High (underestimates time requirements)
Sunk Cost Fallacy: Low (willing to cut losses) Environmental & Lifestyle Factors
Sleep: 6.5/10 quality, 7 hours average
Nutrition: 7/10 (balanced, but afternoon sugar)
Exercise: 5/10 (3x/week, inconsistent)
Stress: 6/10 (moderate work pressure)
Mental Stimulation: 7/10 (varied but not challenging) Improvement Priorities
1. Primary: Increase sustained attention to 40+ minutes
2. Secondary: Boost creative fluency to 20+ ideas/10min
3. Tertiary: Reduce planning fallacy impact
4. Supporting: Improve sleep quality to 8/10
Decision Analysis Log
Append to.learnings/cognition/DECISIONS.md:## [DEC-YYYYMMDD-001] Career Path DecisionDecision Date: 2026-03-12
Importance: High (career direction)
Timeframe: 6-12 month impact
Status: Decided (Option B)
Context & Problem
Choose between:
Option A: Stay current role (stable, limited growth)
Option B: Take promotion (more stress, faster growth)
Option C: Switch companies (unknown, potentially higher pay) Decision Process
1. Information Gathering (3 days)
- Talked to 5 people in similar positions
- Researched market salaries
- Assessed personal tolerance for stress
2. Criteria Weighting
- Growth potential: 30%
- Work-life balance: 25%
- Compensation: 20%
- Learning opportunity: 15%
- Team quality: 10%
3. Option Scoring (1-10 weighted)
- Option A: 6.2 (stable but stagnant)
- Option B: 7.8 (growth, manageable stress)
- Option C: 6.5 (high risk, high potential reward)
4. Cognitive Bias Check
- Status Quo Bias: Considered (Option A attractive due to comfort)
- Loss Aversion: Addressed (willing to risk for growth)
- Overconfidence: Guarded against (consulted others)
- Sunk Cost: Irrelevant (no prior investment)Reasoning & Rationale
Option B chosen because:
1. Aligns with 3-year career goal (management track)
2. Stress increase tolerable (15% vs. 50% more pay)
3. Company investment in my growth (training budget)
4. Backup plan exists (can return to individual contributor if needed)Confidence Level & Uncertainty
Confidence: 8/10 in decision quality
Key Uncertainties:
- Actual stress level in new role (estimated)
- Team dynamics with new reports (unknown)
- Company stability (market conditions)
Contingency Plans:
- 3-month review: If stress > 7/10, implement coping strategies
- 6-month exit: If miserable, start job search with new titleExpected Outcome vs. Actual Tracking
Expected: 20% skill growth, 50% pay increase, stress +2 points
Actual: [To be filled after 3 months]
Variance Analysis: [To be filled] Cognitive Lessons
1. Bias Management: Successfully resisted status quo bias
2. Decision Quality: Structured approach improved confidence
3. Information Sufficiency: Gathered enough but not too much
4. Emotion Integration: Acknowledged fear but didn't let it decide
Problem-Solving Log
Append to.learnings/cognition/PROBLEMS.md:## [PROB-YYYYMMDD-001] System Architecture Design ProblemProblem Date: 2026-03-12
Complexity: High (multiple constraints, novel requirements)
Time Spent: 8 hours over 2 days
Solution Status: Resolved (hybrid approach)
Problem Definition
Design scalable notification system supporting:
1M+ users
10+ notification types
<100ms latency requirement
99.99% reliability
Cost < $500/month at scale Solution Approaches Considered
1. Approach A: Single monolithic service
- Pros: Simple, fast to build
- Cons: Hard to scale, single point of failure
- Viability: Low (scaling constraints)
2. Approach B: Microservices architecture
- Pros: Scalable, fault-tolerant
- Cons: Complex, operational overhead
- Viability: Medium (over-engineered for MVP)
3. Approach C: Serverless functions + queue
- Pros: Cost-effective, auto-scaling
- Cons: Cold start latency, vendor lock-in
- Viability: High (meets requirements)4. Approach D: Hybrid (Approach C + simple service)
- Pros: Balances scalability and simplicity
- Cons: More moving parts
- Viability: Selected
Breakthrough Insights
1. Core Realization: 80% of notifications are 3 types β optimize those
2. Pattern Recognition: Similar to email sending systems (existing patterns)
3. Constraint Reframing: Reliability requirement actually means "eventual consistency with retries"
4. Simplification: Batch processing acceptable for non-urgent notificationsSolution Architecture
Urgent notifications (<100ms): Dedicated service (5% of traffic)
Standard notifications: Serverless functions + queue (95% of traffic)
Fallback: Retry queue with exponential backoff
Monitoring: Latency and error tracking for each type Cognitive Process Analysis
Initial Impasse: Overwhelmed by constraints (30 minutes stuck)
Breakthrough Method: Whiteboard diagramming β pattern emergence
Critical Thinking: Questioned each requirement's validity
Creative Synthesis: Combined approaches rather than choosing one Performance Metrics
Design Quality: 8/10 (meets all requirements, elegant compromise)
Cognitive Effort: High (complex trade-off analysis)
Time Efficiency: Good (8 hours for complex problem)
Solution Novelty: Medium (adapted existing patterns) Improvement Opportunities
1. Faster Pattern Recognition: Study more system design patterns
2. Better Constraint Analysis: Formalize requirement prioritization
3. Reduced Overthinking: Set timebox for decision making
4. Collaborative Thinking: Involve others earlier for perspective
Bias Identification & Correction
Append to.learnings/cognition/BIASES.md:## [BIAS-YYYYMMDD-001] Confirmation Bias in Project EstimationIdentified: 2026-03-12T14:30:00Z
Bias Type: Confirmation Bias
Context: Software project timeline estimation
Impact: Moderate (2-week underestimation)
Bias Manifestation
Situation: Estimating new feature development time
Behavior: Sought evidence supporting optimistic timeline
Ignored: Previous similar projects that took longer
Result: 4-week estimate (actual likely 6 weeks) Detection Process
1. Trigger: Felt too confident about estimate
2. Check: Asked "What evidence contradicts this?"
3. Discovery: Found 3 similar past projects averaged 6 weeks
4. Recognition: Realized seeking confirming evidence onlyCorrection Applied
1. Forced Consideration: Listed all past similar projects
2. Outsider View: Asked "What would I estimate for someone else?"
3. Pre-mortem: Imagined project failed, identified causes
4. Adjustment: Revised to 6 weeks with risk bufferRoot Cause Analysis
Motivation: Wanted to please stakeholders with fast timeline
Pattern: Recurring in estimation situations (3rd instance this year)
Environment: Pressure to deliver quickly, reward for optimism
Cognitive Style: Prefers action over caution Prevention Strategy
1. Checklist: Always review past similar projects before estimating
2. Devil's Advocate: Assign someone to challenge optimistic estimates
3. Buffer Rule: Add 30% to initial optimistic estimate
4. Calendar Review: Monthly review of estimates vs. actualsBias Strength Assessment
Before Correction: 8/10 (strong bias influence)
After Correction: 3/10 (minimal residual influence)
Improvement: 5-point reduction through structured process
Durability: Expected to last 2-3 months before reinforcement needed Related Biases to Monitor
Planning Fallacy: Often co-occurs with confirmation bias
Optimism Bias: Similar root in underestimating difficulties
Anchoring: Initial estimate anchors subsequent thinking
Cognitive Training Framework
Attention Training Protocol
Memory Enhancement System
Logical Reasoning Exercises
Creativity Development
Metacognition Building
Cognitive Performance Factors
Lifestyle Optimization
Environmental Design
Cognitive Load Management
Integration with Other Skills
With Self-Improving-Learning
With Self-Improving-Work
With Self-Improving-Habit
Success Metrics
Performance Metrics
Process Metrics
Outcome Metrics
Getting Started
Step 1: Cognitive Baseline (Week 1)
1. Complete baseline assessment across 5 dimensions 2. Identify top 2 cognitive strengths and weaknesses 3. Select 1-2 priority areas for improvement 4. Establish initial metrics and tracking systemStep 2: Targeted Training (Weeks 2-4)
1. Implement specific exercises for priority areas 2. Daily tracking of cognitive performance metrics 3. Weekly review of progress and adjustments 4. Environmental optimization for cognitive supportStep 3: Integration & Maintenance (Month 2+)
1. Incorporate cognitive techniques into daily work/life 2. Regular bias checks in important decisions 3. Quarterly reassessment of cognitive fitness 4. Continuous refinement of thinking strategiesScientific Foundation
Based on:
Integration Note: This skill provides the thinking toolkit for other self-improving skills, ensuring decisions and problem-solving are based on clear, bias-aware cognition rather than intuition or habit alone.