Runstr analytics

Other

Advanced RUNSTR fitness analytics with trend analysis, performance insights, training recommendations, and correlation tracking. Analyzes workout history, habits, mood, and steps to provide personalized coaching insights and identify patterns in training effectiveness.

Install

openclaw skills install runstr-analytics

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

Flag	Description
`--nsec`	Your Nostr private key (nsec1...)
`--days`	Analysis period (default: 30)
`--insights`	Generate improvement tips
`--coaching-report`	Full coaching analysis
`--training-plan`	Path to training plan markdown file
`--trends`	Show trend visualizations
`--correlations`	Analyze habit/mood correlations
`--pb`	Show personal records
`--challenges`	Generate weekly challenges

Data Sources

Nostr Encrypted Backup (Kind 30078): Primary workout, habit, journal data
Local Cache: SQLite database for fast re-analysis
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