estimation

Estimate task effort with confidence intervals using three-point estimation.

Updated Feb 3, 2026
One-click install
npx skills add https://github.com/dhruvinrsoni/agentskills-garden --skill estimation-dhruvinrsoni
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: estimation
Source: https://github.com/dhruvinrsoni/agentskills-garden/tree/main/skills/20-planning/estimation
Command: npx skills add https://github.com/dhruvinrsoni/agentskills-garden --skill estimation-dhruvinrsoni

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill tackles the challenge of providing realistic effort estimates for tasks, moving beyond simple guesses to data-driven projections with clear uncertainty.

Core Features & Use Cases

  • Accurate Effort Estimation: Generates time-based estimates for subtasks and overall projects.
  • Uncertainty Quantification: Expresses estimates as ranges with confidence intervals (68% and 95%).
  • Use Case: When planning a new software feature, use this Skill to estimate the development time, providing stakeholders with a clear understanding of the potential range of effort and the factors contributing to uncertainty.

Quick Start

Use the estimation skill to generate a three-point estimate for the 'user-authentication' subtask.

Frequently Asked Questions about estimation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create effort estimates with confidence intervals instead of single point guesses?▼

Effort estimation with confidence intervals applies three-point estimation techniques and historical data calibration to generate probabilistic ranges. It expresses task effort at 68% and 95% confidence levels rather than relying on single point guesses.

What is PERT-based three-point estimation and when should I use it for project planning?▼

PERT-based three-point estimation is a probabilistic forecasting technique that scopes task decomposition and relative sizing. Use it during risk-aware planning to communicate uncertainty drivers and provide data-driven effort projections for software features and subtasks.

How do I quantify uncertainty and calculate risk for software development task estimates?▼

Quantifying uncertainty for software development tasks involves calibrating three-point estimates against historical data. This risk-aware planning approach generates effort projections with explicit 68% and 95% confidence intervals to communicate uncertainty drivers to stakeholders.

Can I use historical data to calibrate effort estimates for new software features?▼

Yes, calibrating effort estimates against historical data is supported for new software features. By applying three-point estimation techniques to past project metrics, the skill generates calibrated time-based projections with clear confidence intervals for subtasks and overall projects.

Does task decomposition improve the accuracy of relative sizing and effort estimation?▼

Task decomposition directly improves effort estimation accuracy by scoping complex features into manageable subtasks. This enables precise relative sizing and allows three-point estimation techniques to generate tighter, more reliable confidence intervals for project planning.

What are the limitations of probabilistic forecasting for effort estimation in risk-aware planning?▼

Probabilistic forecasting limitations stem from the quality of historical data calibration and task decomposition. If relative sizing inputs are poor or uncertainty drivers are misunderstood, the resulting 68% and 95% confidence intervals will not accurately reflect true project risk.