runstr-analytics（运行分析）

RUNSTR Analytics Skill

Advanced fitness analytics and coaching insights for RUNSTR data. Provides trend analysis, performance tracking, habit correlation, and personalized training recommendations.

Setup

Required: RUNSTR_NSEC environment variable

This skill requires your Nostr private key (nsec1...) to decrypt RUNSTR backup data.

Option 1 - For OpenClaw/chat usage: Tell your bot: "Here's my RUNSTR nsec: nsec1..."

Option 2 - For CLI/cron automation:

export RUNSTR_NSEC="nsec1..."

⚠️ Security note: The nsec is passed securely via stdin (not CLI arguments) to prevent exposure in process lists. Cache files use restrictive permissions (0700/0600).

Features

• Advanced Trend Analysis: Pace trends by activity type, seasonal comparisons, training load tracking
• Performance Insights: Personal records, weekly challenges, streak tracking
• Correlation Analysis: Mood vs training, habits vs performance, sleep vs recovery
• Training Recommendations: AI-driven tips for improvement, goal-based planning
• Training Plan Integration: Sync with external training plans, track adherence

Quick Start

Extended version (recommended - with local cache):

# First run - fetch from Nostr and cache locally
python3 scripts/analyze_extended.py --nsec <NSEC> --days 60 --insights --force-refresh

# Subsequent runs - use cached data (no nsec needed!)
python3 scripts/analyze_extended.py --days 60 --insights

Lightweight version (basic analysis):

python3 scripts/analyze_light.py --nsec <NSEC> --days 30 --insights

Full version (requires pandas, numpy, scipy):

# Install dependencies first: pip3 install pandas numpy scipy
python3 scripts/analyze.py --nsec <NSEC> --days 60 --coaching-report

Commands

Data Sources

1. Nostr Encrypted Backup (Kind 30078): Primary workout, habit, journal data
2. Local Cache: SQLite database for fast re-analysis
3. Training Plans: Markdown files with structured training schedules

Extended Features (analyze_extended.py)

Local Cache

• SQLite database stores workouts locally
• Fast subsequent analyses (no Nostr query needed)
• Automatic PR tracking across sessions
• Cache location: ~/.cache/runstr-analytics/

Week-to-Week Comparison

# Shows last 4 weeks with trends
python3 scripts/analyze_extended.py --insights

Personal Records

• Automatically detects PRs for: 1K, 5K, 10K, Half Marathon
• Stores historical PRs in cache
• Shows date and pace for each PR

Visual Charts

• ASCII bar charts for weekly stats
• Sparkline trend indicators (📈 📉 ➡️)
• Easy visual comparison between weeks

Automated Daily Updates

# Set up daily cron job (runs at 07:00)
./setup_cron.sh

# View latest automated report
./view_report.sh

# Check update logs
tail -f ~/.cache/runstr-analytics/daily_update.log

The automation will:

• Check if cache is older than 12 hours
• Fetch fresh data from Nostr if needed
• Generate new report with charts
• Save to ~/.cache/runstr-analytics/latest_report.txt

Usage Examples

# First time setup - fetch and cache
python3 scripts/analyze_extended.py --nsec nsec1... --force-refresh

# Daily check - uses cache
python3 scripts/analyze_extended.py --insights

# Analyze last 90 days
python3 scripts/analyze_extended.py --days 90 --insights

# Force re-fetch from Nostr (after new backup)
python3 scripts/analyze_extended.py --nsec nsec1... --force-refresh

# Set up automatic daily updates
./setup_cron.sh

# View today's automated report
./view_report.sh

Analytics Engine

Trend Calculations

• Rolling averages (7-day, 30-day)
• Week-over-week comparisons
• Pace progression by distance bracket
• Training load (acute vs chronic)

Correlation Analysis

• Pearson correlation for numeric relationships
• Mood distribution by activity type
• Habit impact on performance metrics

Recommendation Engine

• Rule-based coaching tips
• Goal gap analysis
• Recovery recommendations

Output Formats

• Terminal tables (default)
• JSON export (--format json)
• Markdown reports (--format md)

Security Considerations

Private Key Handling

• RUNSTR_NSEC is your Nostr private key — treat it like a password. Never share it.
• This skill passes the key via stdin (not command-line arguments) to prevent exposure in process lists (ps)
• For added security on multi-user systems, ensure your system is not configured to log environment variables

Local Data Protection

• Decrypted workout/journal data is cached locally in ~/.cache/runstr-analytics/runstr_cache.db
• Cache directory and database files are created with restrictive permissions (0700/0600) — only your user can access them
• Ensure your disk is encrypted (full-disk encryption) for maximum protection

Recommended Installation

• Install on a personal machine with restricted access (single user, disk encryption enabled)
• Consider pinning the nak binary to a specific release rather than using @latest
• Review the cron setup before enabling automatic daily updates

Privacy

• NSEC is never stored or logged in skill output
• All processing happens locally on your machine
• Nostr queries use encrypted connections (WSS/WebSocket Secure)
• No data is sent to external analytics services