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estimate

Analyze complexity, dependencies, and sprint data to estimate task effort.

Updated Apr 10, 2026
Search Tags:#code-analysis#velocity#sprint-planning#risk-analysis#estimate#effort-estimation
One-click install
npx skills add https://github.com/emcconnell/nova-scout --skill estimate-emcconnell
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: estimate
Source: https://github.com/emcconnell/nova-scout/tree/main/.claude/skills/estimate
Command: npx skills add https://github.com/emcconnell/nova-scout --skill estimate-emcconnell

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Estimating engineering and product task effort is often subjective, inconsistent, and lacks traceable rationale; this Skill provides a reproducible, evidence-based estimate by analyzing complexity, dependencies, historical velocity, and risk factors.

Core Features & Use Cases

  • Automatic task scoping: Reads a task description and identifies affected systems, likely files, and integration points.
  • Complexity & risk analysis: Assesses code complexity, coupling, test coverage needs, and performance or integration risks.
  • Historical comparison: Uses past sprint data and velocity to ground optimistic, expected, and pessimistic timeboxes.
  • Deliverable output: Produces a structured estimate with recommended budget, confidence level, risk table, dependencies, and a suggested subtask breakdown for sprint planning.
  • Use case: Product managers or engineering leads can request an estimate for a new gameplay feature, bugfix, or refactor and receive a ready-to-review estimate and mitigation suggestions.

Quick Start

Estimate the effort to implement "add missile lock mechanic and ammo counter UI" including tests and integration with existing player systems.

Frequently Asked Questions about estimate

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

FAQPage Schema
How do I estimate effort for development tasks using historical sprint velocity and code complexity?▼

Effort estimation analyzes task complexity, dependencies, test coverage, and historical sprint velocity to produce structured time estimates. It reads project documents and past sprint data to generate optimistic, expected, and pessimistic time ranges with confidence levels for implementation tasks, bug fixes, and infrastructure work.

What is the best way to generate structured time estimates with risk analysis for sprint planning?▼

Structured estimates with risk analysis are generated by assessing code complexity, coupling, and integration risks alongside historical velocity data. The output includes a risk matrix, affected systems, likely files, confidence level, dependencies, and suggested subtask breakdowns to support sprint planning decisions.

Can I get optimistic, expected, and pessimistic timeboxes for a feature change based on past sprint data?▼

Yes, optimistic, expected, and pessimistic timeboxes are produced by comparing task complexity against historical velocity and sprint data. The analysis grounds time estimates in past performance while factoring in code complexity, dependencies, and integration risks.

Does effort estimation work for bug fixes and refactoring tasks or only new feature development?▼

Effort estimation applies to implementation tasks, bug fixes, feature changes, and infrastructure work. It analyzes code, design docs, and sprint history to assess complexity, test coverage needs, and risk factors regardless of the development task type.

How do I break down a complex development task into subtasks with confidence levels for sprint planning?▼

Complex tasks are broken down by analyzing affected systems, integration points, and code complexity to produce a suggested subtask breakdown. Each estimate includes a confidence level, risk table, and dependency map derived from project documents and historical sprint velocity data.

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