# Feature Prioritization

> Prioritize features by outcome value, learning value, dependency order, risk, and complexity. Use when turning a feature map into a build order or reviewing whether a backlog is tactical and too feature-first.

- Skill: `harsh817/feature-prioritization` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add harsh817/feature-prioritization`
- Raw SKILL.md: https://api.skillmd.com/api/skills/harsh817/feature-prioritization/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Product & Planning
- Author: harsh817 (https://skillmd.com/u/harsh817)
- Updated: 2026-09-21
- Page: https://skillmd.com/skills/harsh817/feature-prioritization

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# Feature Prioritization

## Definition

Order features so each increment teaches something useful, protects design quality, and moves toward the outcome. Prioritization is not only value ranking; it also considers dependencies, abstraction discovery, risk, and validation.

## Questions To Ask

- Which feature proves the core outcome fastest?
- Which feature removes the largest unknown?
- Which dependency must exist before others?
- Which feature is risky enough to test early?
- Which feature can wait without blocking learning?

## Existing Project Comparison

- Compare planned order with current technical dependencies and tests.
- Identify features blocked by missing abstractions or rules.
- Flag high-priority features that would force tactical shortcuts.
- Move risk-reducing spikes or slices earlier when they protect architecture.

## Suggestive Plan

1. Score each feature for outcome value, learning value, risk reduction, dependency need, and complexity cost.
2. Identify mandatory first slices.
3. Put abstraction-revealing work before broad surface area.
4. Defer nice-to-have features.
5. Produce an ordered build list with rationale.

## Example

Build "submit appointment request" before "staff dashboard filters" because it proves the core journey and reveals scheduling rules.

## Vocabulary

- Outcome value: contribution to the desired result.
- Learning value: how much uncertainty a feature removes.
- Risk reduction: early work that prevents expensive later discovery.
- Dependency: feature or rule another feature requires.
- Tactical priority: ordering chosen only because it is quick.

## Expected Outcome

Produce a prioritized feature list with reason, dependencies, risk, estimated complexity, and suggested build order.