Menu

Individual skill

80-20-feature-prioritization

Use this skill when scoping a roadmap, prioritizing features, planning an MVP, or deciding what to ship and what to defer. Trigger when the user asks "what should we build next?", "is this feature worth it?", "should we ship feature X?", or when reviewing a feature backlog. Sub-aspect of `80-20-rule`; read that first.

plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/80-20-feature-prioritization/SKILL.md

Read pinned source

Source commit d780783eba4ecc7c8b9429f95c9362df95f07c61

What was checked

Matches the observed repository HEAD
Yes
Scanner rules are current
Yes
Repository scan complete
No
Skill scan complete
No
Observed behavior
Network or broad shell
Last checked
Nov 4, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.

Repository context

Repository stars (not skill ratings)
1,532
Repository last updated
Nov 6, 2026
License
Apache-2.0

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files
Read excerpt

# 80/20 in feature prioritization

The most direct application of the 80/20 rule: deciding which features to invest in. Most products accumulate features over time; many of those features see little use. The discipline is identifying the critical fraction worth deepening and the long tail worth either tucking or removing.

## The prioritization framework

For each feature (proposed or existing), gather:

### 1. Usage signal

If the feature exists: how many users engage with it? How often? Is engagement growing or declining?

If the feature is proposed: how many users say they want it? Is that signal coming from a vocal minority or a representative sample?