feature-prioritizer
SkillAI & modelsScore a feature list using RICE (Reach, Impact, Confidence, Effort) and return a ranked table with recommendation. Use when the user wants to prioritize features, decide what to build next, or cut scope.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the feature-prioritizer skill
What this skill tells your AI
The instructions your AI receives, as published by hamzafarooq/claude-code-starter in .claude/skills/feature-prioritizer/SKILL.md and read by ahel’s review.
Ask the user:
- "Paste your list of features or initiatives."
- "What's the timeframe — one quarter, one sprint, one year?"
- "Any features that are already committed or non-negotiable? I'll mark them separately."
For each feature, estimate:
- Reach — how many users affected per period (1–10 scale or absolute number)
- Impact — how much does it move the needle per user (0.25 = minimal, 0.5 = low, 1 = medium, 2 = high, 3 = massive)
- Confidence — how sure are you about Reach and Impact? (percentage: 50%, 80%, 100%)
- Effort — person-months to build (use your best estimate; flag if unclear)
RICE score = (Reach × Impact × Confidence) / Effort
Feature Prioritization — [Product / Quarter]
| Feature | Reach | Impact | Confidence | Effort | RICE Score | Priority |
|---|---|---|---|---|---|---|
| [feature] | [#] | [#] | [%] | [months] | [score] | HIGH/MED/LOW |
Recommended build order
Top 3 features with one-line rationale for each.
Features to cut or defer
Which items scored low and why you should drop or delay them.
What the scores can't tell you
Flag 1–2 strategic or political factors that aren't captured in RICE but matter for the decision.
State your assumptions clearly. Ask: "Want me to re-score with different estimates?"
Signals
- GitHub stars
- 143
- Forks
- 40
- Last commit
- Jul 2026
Others that do the same job
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feature-prioritizer- Source
- github.com/hamzafarooq/claude-code-starter