aj-geddes/useful-ai-prompts

project-estimation

Estimate project scope, timeline, and resource requirements using multiple estimation techniques including bottom-up, top-down, and analogous estimation methods for accurate project planning.

First seen Jan 21, 2026

Installation

$ npx skills add aj-geddes/useful-ai-prompts --skill project-estimation

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Repository health

Stars 334
License LICENSE
Default branch main
Open issues 1
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,455 B
  • docs SUMMARY.md 3,272 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 629 installs

SKILL.md

Project Estimation

Table of Contents

  • [Overview](#overview)
  • [When to Use](#when-to-use)
  • [Quick Start](#quick-start)
  • [Reference Guides](#reference-guides)
  • [Best Practices](#best-practices)

Overview

Accurate project estimation determines realistic timelines, budgets, and resource allocation. Effective estimation combines historical data, expert judgment, and structured techniques to minimize surprises.

When to Use

  • Defining project scope and deliverables
  • Creating project budgets and timelines
  • Allocating team resources
  • Managing stakeholder expectations
  • Assessing project feasibility
  • Planning for contingencies
  • Updating estimates during project execution

Quick Start

Minimal working example:

# Three-point estimation technique for uncertainty

class ThreePointEstimation:
    @staticmethod
    def calculate_pert_estimate(optimistic, most_likely, pessimistic):
        """
        PERT formula: (O + 4M + P) / 6
        Weighted toward most likely estimate
        """
        pert = (optimistic + 4 * most_likely + pessimistic) / 6
        return round(pert, 2)

    @staticmethod
    def calculate_standard_deviation(optimistic, pessimistic):
        """Standard deviation for risk analysis"""
        sigma = (pessimistic - optimistic) / 6
        return round(sigma, 2)

    @staticmethod
    def calculate_confidence_interval(pert_estimate, std_dev, confidence=0.95):
        """
        Calculate confidence interval for estimate
        95% confidence ≈ ±2 sigma
        """
        z_score = 1.96 if confidence == 0.95 else 2.576
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

Guide Contents
[Three-Point Estimation (PERT)](references/three-point-estimation-pert.md) Three-Point Estimation (PERT)
[Bottom-Up Estimation](references/bottom-up-estimation.md) Bottom-Up Estimation
[Analogous Estimation](references/analogous-estimation.md) Analogous Estimation
[Resource Estimation](references/resource-estimation.md) Resource Estimation
[Estimation Templates](references/estimation-templates.md) Estimation Templates

Best Practices

✅ DO

  • Use multiple estimation techniques and compare results
  • Include contingency buffers (15-25% for new projects)
  • Base estimates on historical data from similar projects
  • Break down large efforts into smaller components
  • Get input from team members doing the actual work
  • Document assumptions and exclusions clearly
  • Review and adjust estimates regularly
  • Track actual vs. estimated metrics for improvement
  • Include non-development tasks (planning, testing, deployment)
  • Account for learning curve on unfamiliar technologies

❌ DON'T

  • Estimate without clear scope definition
  • Use unrealistic best-case scenarios
  • Ignore historical project data
  • Estimate under pressure to hit arbitrary targets
  • Forget to include non-coding activities
  • Use estimates as performance metrics for individuals
  • Change estimates mid-project without clear reason
  • Estimate without team input
  • Ignore risks and contingencies
  • Use one technique exclusively