Skip to main content

progressive-estimation

Estimate AI-assisted and hybrid human+agent development work with research-backed PERT statistics and calibration feedback loops

Jump to install

Source facts

Repository
muhammedadnank/Antigravity-Skills
Last source activity
June 6, 2026 at 18:30
Detected SKILL.md language
English
Stars
13
Forks
1

Install options

The review-first prompt is selected by default. You can switch to a direct command or download a local copy.

Review the source files

Read SKILL.md and any companion files shown by SkillsMP before deciding whether to install.

Showing SKILL.md

SKILL.md
Source instructions ยท Read-only preview
name
progressive-estimation
description
Estimate AI-assisted and hybrid human+agent development work with research-backed PERT statistics and calibration feedback loops
category
project-management
risk
safe
source
community
date_added
2026-03-10
author
Enreign
tags
["estimation","project-management","pert","sprint-planning","ai-agents"]
tools
["claude"]
# Progressive Estimation Estimate AI-assisted and hybrid human+agent development work using research-backed formulas with PERT statistics, confidence bands, and calibration feedback loops. ## Overview Progressive Estimation adapts to your team's working mode โ€” human-only, hybrid, or agent-first โ€” applying the right velocity model and multipliers for each. It produces statistical estimates rather than gut feelings. ## When to Use This Skill - Estimating development tasks where AI agents handle part of the work - Sprint planning with hybrid human+agent teams - Batch sizing a backlog (handles 5 or 500 issues) - Staffing and capacity planning with agent multipliers - Release date forecasting with confidence intervals ## How It Works 1. **Mode Detection** โ€” Determines if the team works human-only, hybrid, or agent-first 2. **Task Classification** โ€” Categorizes by size (XSโ€“XL), complexity, and risk 3. **Formula Application** โ€” Applies research-backed multipliers grounded in empirical studies 4. **PERT Calculation** โ€” Produces expected values using three-point estimation 5. **Confidence Bands** โ€” Generates P50, P75, P90 intervals 6. **Output Formatting** โ€” Formats for Linear, JIRA, ClickUp, GitHub Issues, Monday, or GitLab 7. **Calibration** โ€” Feeds back actuals to improve future estimates ## Examples **Single task:** > "Estimate building a REST API with authentication using Claude Code" **Batch mode:** > "Estimate these 12 JIRA tickets for our next sprint" **With context:** > "We have 3 developers using AI agents for ~60% of implementation. Estimate this feature." ## Best Practices - Start with a single task to calibrate before moving to batch mode - Feed back actual completion times to improve the calibration system - Use "instant mode" for quick T-shirt sizing without full PERT analysis - Be explicit about team composition and agent usage percentage ## Common Pitfalls - **Problem:** Overconfident estimates **Solution:** Use P75 or P90 for commitments, not P50 - **Problem:** Missing context **Solution:** The skill asks clarifying questions โ€” provide team size and agent usage - **Problem:** Stale calibration **Solution:** Re-calibrate when team composition or tooling changes significantly ## Related Skills - `@sprint-planning` - Sprint planning and backlog management - `@project-management` - General project management workflows - `@capacity-planning` - Team velocity and capacity planning ## Additional Resources - [Source Repository](https://github.com/Enreign/progressive-estimation) - [Installation Guide](https://github.com/Enreign/progressive-estimation/blob/main/INSTALLATION.md) - [Research References](https://github.com/Enreign/progressive-estimation/tree/main/references) ## Limitations - Use this skill only when the task clearly matches the scope described above. - Do not treat the output as a substitute for environment-specific validation, testing, or expert review. - Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
View on GitHub