How does the skill account for technical risks?

It provides standardized multipliers for common risks, such as adding 50-100% for legacy code modifications or 25-50% for new technology learning curves.

Can this skill help with Agile story points?

Yes, it includes a calibration guide for Fibonacci story points (1-13) and helps teams establish a baseline reference story for consistent sizing.

What is the 'Cone of Uncertainty' feature?

It is a framework that helps you communicate to stakeholders how estimate ranges narrow from initial concepts (4x range) to completed requirements (2x range) to final design (1.2x range).

What is the PERT estimation method used in this skill?

The skill uses the Program Evaluation and Review Technique (PERT), which calculates a weighted average: (Optimistic + 4*Expected + Pessimistic) / 6, providing a more balanced view than a single-point estimate.

Engineering Estimation

Name: Engineering Estimation
Author: chavangorakh1999

bychavangorakh1999

0•

Collaboration Tools

Calculates realistic software engineering effort using PERT formulas, risk-adjusted sizing, and the cone of uncertainty.

The Engineering Estimation skill provides a rigorous framework for software sizing, helping teams move away from gut-feeling guesses toward data-driven forecasting. By utilizing Three-Point Estimation (PERT) and the 'Cone of Uncertainty,' it allows developers to communicate uncertainty honestly to stakeholders while accounting for hidden complexities like legacy code or undocumented APIs. It includes built-in logic for story point calibration, velocity tracking, and risk registration, ensuring that every estimate includes the necessary buffers for a successful delivery.

Key Features

01Three-Point Estimation (PERT) calculation for optimistic, expected, and pessimistic outcomes

02Risk-adjustment factors for legacy code, technical debt, and external dependencies

03Cone of Uncertainty tracking to refine estimate accuracy throughout the project lifecycle

04Story point calibration using Fibonacci sequences and team velocity metrics

05Standardized output format including risk registers and scope assumptions

060 GitHub stars

Use Cases

01Sizing a complex new feature during sprint planning to ensure realistic commitments

02Calibrating team velocity and capacity based on historical performance and 'yesterday's weather'

03Generating project timelines for stakeholders that account for technical risks and unknowns

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add chavangorakh1999/sde-skills estimation

For use in Claude.ai and ChatGPT

Key Features

01Three-Point Estimation (PERT) calculation for optimistic, expected, and pessimistic outcomes

02Risk-adjustment factors for legacy code, technical debt, and external dependencies

03Cone of Uncertainty tracking to refine estimate accuracy throughout the project lifecycle

04Story point calibration using Fibonacci sequences and team velocity metrics

05Standardized output format including risk registers and scope assumptions

060 GitHub stars

Use Cases

01Sizing a complex new feature during sprint planning to ensure realistic commitments

02Calibrating team velocity and capacity based on historical performance and 'yesterday's weather'

03Generating project timelines for stakeholders that account for technical risks and unknowns