Quantify growth, task completion, learning, and achievements into numeric progress.
npx skills add https://github.com/SJTU-IPADS/SkVM-data --skill quantified-self
Please help me install this Agent Skill. Skill: quantified_self Source: https://github.com/SJTU-IPADS/SkVM-data/tree/main/skills/growth-tracker Command: npx skills add https://github.com/SJTU-IPADS/SkVM-data --skill quantified-self
Quantified Self provides a data-driven framework to quantify AI growth, task completion, learning outcomes, and efficiency, turning subjective progress into concrete numbers that guide improvement.
Initialize the quantified_self data model and begin automatic tracking of growth, tasks, and learning.
High-intent search queries and answers about installing and using this skill.
Track AI learning outcomes and task completion rates by initializing a structured data model that automatically quantifies growth, tasks, and learning milestones into numeric progress. The framework catalogs new concepts, mastery levels, and completion statistics.
Quantified self data tracking for AI growth is a framework that turns subjective progress into concrete numbers. It measures knowledge, capability, quality, and efficiency to provide clear percentile progress and trend visuals for improvement.
Yes, you can perform efficiency analysis covering response times, iteration counts, and tool usage while storing data locally. Local private data storage ensures all growth tracking and configurable reporting protect your privacy.
Visualize task statistics and growth progress by applying a structured data model with modular components. It enforces frontmatter-driven discovery to generate distribution by task type, completion rates, and trend visuals.
Yes, quantified self tracking works without external dependencies. It enforces a structured data model and stores data locally, requiring no additional components to measure achievements, goals, and daily stats.
The best way to track milestones and achievements for performance reviews is using a data-driven framework that quantifies learning and efficiency. It provides milestone highlights, progress updates, and numeric progress to guide improvement.
d-kimusonOrchestrate subagents for task planning, delegation, and progress tracking.
FassadenFixGenerates themed Excel workbooks with charts and templates using openpyxl.
ovachieverCreate and manipulate chunked N-dimensional arrays with NumPy, Dask, and Xarray.
rwHiveAquaTransform startup user data into validated insights for pivots and growth.
