Calculates and tracks human-equivalent time estimates for every development task performed by Claude.
The Estimation Tracker skill enforces a rigorous time-estimation protocol for all AI interactions, requiring Claude to predict how long a competent human developer would take to complete a task manually. By injecting hidden metadata into every response, it enables teams to benchmark AI productivity, compare model accuracy, and gain data-driven insights into the real-world efficiency gains of AI-assisted development across features, bug fixes, and refactors. This skill is essential for organizations looking to quantify the ROI of AI tools while improving project management predictability.
Key Features
01Support for granular time units including minutes, hours, and days
020 GitHub stars
03Hidden metadata injection using standardized HTML comments
04Mandatory human-time estimation for all development tasks
05Data-driven benchmarking for AI-assisted productivity tracking
06Comprehensive scope accounting including planning, coding, and testing
Use Cases
01Improving team capacity planning and software delivery timelines
02Benchmarking AI speed and efficiency against traditional manual development
03Analyzing AI performance across different types of coding tasks and refactors
