Analyzes tracked behaviors and outcomes to generate actionable insights and data-driven feedback loops.
This skill transforms Claude into a data analyst for personal and system performance, helping users extract meaningful signal from raw tracking logs. It provides a structured framework for daily glances, weekly audits, and monthly evaluations, automating the calculation of behavior compliance and trend identification. By comparing leading indicators to lagging outcomes and providing pre-built Supabase SQL queries, it enables users to tighten their feedback loops, identify friction points in their habits, and make evidence-based adjustments to their workflows.
Key Features
01Multi-cadence review templates for daily, weekly, and monthly tracking.
02Directional trend analysis comparing current data against 4-week historical averages.
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04Integrated Supabase SQL queries for efficient data extraction and log analysis.
05Leading vs. Lagging indicator analysis to correlate behavior changes with outcomes.
06Automated compliance calculation using (days executed / days intended) metrics.
Use Cases
01Performing a weekly habit audit to identify which behaviors are meeting the 80% compliance threshold.
02Extracting insights from tracking data to decide which metrics to continue, investigate, or stop tracking.
03Analyzing monthly target progress to evaluate if current systems and algorithms are producing desired results.
