Nobody Cares - Daily Improvement Hub

A modular system for tracking daily activities, building skills portfolios, analyzing trading performance, and generating shareable artifacts. Built for incremental value over time.

Your Edge System: Track your unique intuition, connect insights across domains (trading, sports, code), and learn from YOUR patterns - not generic formulas.

Quick Start

New to this? See QUICKSTART.md for a 5-minute getting started guide.
Not sure when to log? See WHEN_TO_LOG.md for practical examples and a checklist.
Understanding the codebase? See INDEX.md for repository structure and extension points.
Extended documentation? See docs/ folder for additional technical docs.

Basic commands:

# Quick capture (when overwhelmed)
nc q 100 "houston bet"

# Full context (when you have time)
nc risk sports_bet --cost 100 --odds 3.21 --my-probability 0.45 --what-i-saw "Market slow" "Value bet"

# List your risks
nc risks

# See today's activity
nc today

Key Features

Your Edge System

• Agency & Ownership Tracking: Binary data (mine/influenced/performed, aligned/not aligned, voluntary/pressure)
• Influence Surface: Track who gets access to influence you (voices_present array)
• Motivation Integrity: Classification (internal/external, alignment/expectation/avoidance/pruning)
• Structured Intuition: Observable patterns (what_i_saw, why_it_mattered) - not feelings
• Pattern Detection: Longitudinal patterns (misalignment, drift, ownership correlation)
• Cross-Domain Connections: Link sports betting to trading, alpha, code
• Multi-Currency Support: Track any currency (USD, ETH, BTC, SOL, etc.) with gas fee tracking
• Cash-Out Tracking: Track when you can't cash out - where value gets lost
• Quick Capture Mode: Ultra-fast entry when overwhelmed (nc q <cost> <notes>)

Content Generation

• One Source, Many Outputs: Generate Twitter, LinkedIn, blog from same entry
• Brevity Control: High/medium/low - system helps you be concise
• Lesson Extraction: Automatically extract hard-won lessons from outcomes
• Distribution: Prepare content for multiple platforms

Review & Iterate

• Pattern Detection: Detect misalignment patterns, drift patterns, ownership correlation
• Learning Reviews: Periodic reviews without prompts - must answer authoritatively (nc learn)
• Pattern Export: Export pattern data to CSV for external analysis (nc patterns export)
• Not Daily Habits: Frequent review cycles, adapt system to YOUR process
• Usage Analytics: See what you use vs skip
• System Adaptation: Remove unused complexity, add what you need
• Examples Library: See what others do, stay grounded

Architecture

• Phase 1: Daily entry foundation ✅
• Phase 2: Web3 alpha brief generator ✅
• Phase 3: Automated data collection ✅
• Phase 4: Trading performance analysis ✅
• Phase 5: Skills & monetization tracking ✅
• Phase 6: Improvement tracking & templates ✅
• Phase 7: Output generation suite ✅
• Phase 8: Pattern recognition & insights ✅
• Phase 9: Your Edge System (sports betting, intuition tracking, multi-currency) ✅

Development

# Run tests
pytest

# Run tests with coverage
pytest --cov=src --cov-report=html

# Format code
black src/

# Type check
mypy src/

Testing

The project includes comprehensive tests covering:

• Core Models (tests/test_models.py): Entry, Project, Improvement, RiskEntry models
• Storage Layer (tests/test_storage.py): Database operations, CRUD for all entities
• CLI Commands (tests/test_cli.py): All CLI commands including risk tracking
• Risk Tracking (tests/test_risk_tracking.py): Risk entry logging, reward updates, opportunity cost tracking
• Data Importers (tests/test_importers.py): CSV parsing and trading performance analysis
• Output Generators (tests/test_outputs.py): Twitter, LinkedIn, video script generation
• Alpha Brief (tests/test_alpha.py): Alpha brief generation and formatting
• Utilities (tests/test_utils.py): Helper functions

Run all tests:

pytest tests/ -v

Run specific test file:

pytest tests/test_storage.py -v

Run with coverage:

pytest --cov=src --cov-report=term-missing

Error Handling & Fallbacks

The system includes comprehensive error handling:

• Input Validation: Probabilities (0-1), costs (>0), odds (>0) with helpful error messages
• Graceful Degradation: Missing metadata handled, defaults provided
• Storage Errors: Try/catch blocks, helpful error messages
• Multi-Currency: Handles any currency, doesn't break on unknown formats
• Review Prompts: Won't break if database issues occur
• Content Generation: Handles missing data gracefully

All error messages include hints (e.g., "Use 0.45 for 45%, not 45").

Privacy & Security

What you're logging: Risk entries, observations, patterns (structured data)
Where it's stored: Local SQLite database on your machine only (data/nobody_cares.db)
Security: No cloud, no network, no external services - completely local
Public repo, private data: Code is public, your database is ignored by .gitignore
Minimum specs: Python 3.10+, ~1MB per 1000 entries, no special permissions needed

See PRIVACY_SECURITY.md for details.

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Major Shifts

See docs/MAJOR_SHIFTS.md for details on:

• Agency & Ownership tracking (binary data, not narrative)
• Structured intuition fields (observable patterns, not feelings)
• Influence surface tracking (access control, not emotion)
• Pattern detection queries (longitudinal patterns, not mood)

Key Principle: This is a personal signal extraction engine, not a feelings database.