feature-prioritization-assistant

feature-prioritization-assistant is a skill for Claude Code from saski/arnesto. It costs 33 tokens per session (488 once invoked), scanned A, a copy of feature-prioritization-assistant, Unlicense.

A feature-ranking method based on RICE: Reach, Impact, Confidence, and Effort, four estimates used to compare product ideas.

In plain words
What is it for?
Use it to score roadmap features, compare competing ideas, and explain prioritization decisions to stakeholders.
Why use it?
It turns disagreements about what to build next into a documented comparison using expected audience, value, certainty, and work involved.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: installed under .agents/ (shared by several agents).

Good fit Use it to score roadmap features, compare competing ideas, and explain prioritization decisions to stakeholders.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/saski/arnesto/feature-prioritization-assistant
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add saski/arnesto --skill feature-prioritization-assistant
Clone the repo
git clone --depth 1 https://github.com/saski/arnesto

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for feature-prioritization-assistant

README.md
[![agentmods](https://agentmods.dev/badge/skills/saski/arnesto/feature-prioritization-assistant.svg)](https://agentmods.dev/skills/saski/arnesto/feature-prioritization-assistant)
Your own site
<a href="https://agentmods.dev/skills/saski/arnesto/feature-prioritization-assistant"><img src="https://agentmods.dev/badge/skills/saski/arnesto/feature-prioritization-assistant.svg" alt="Measured on agentmods" height="20"></a>
Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 488 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00033 $0.00488
Opus 5 $0.00016 $0.00244
Sonnet 5 $0.00007 $0.00098
Haiku 4.5 $0.00003 $0.00049

Measured 8d ago against content hash fe6577f032d9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

feature-prioritization-assistant scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to feature-prioritization-assistant — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/feature-prioritization-assistant/SKILL.md · 54 lines

How it starts

The opening of the file, as written. The whole thing — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Domain Context

This skill implements a proven product management framework. The approach combines best practices from industry leaders and is designed for practical application in day-to-day PM work.

Input Requirements

  • Context about your product, feature, or problem
  • Relevant data, research, or constraints (recommended but optional)
  • Clear articulation of what you're trying to achieve

Feature Prioritization Assistant

When to Use

  • Building your product roadmap
  • Need to choose between multiple feature ideas
  • Stakeholders are debating which features to build first
  • Want to make data-driven prioritization decisions
  • Need to justify prioritization decisions to leadership

What This Skill Does

Helps you systematically evaluate and prioritize features using the RICE framework (Reach, Impact, Confidence, Effort), providing scores and recommendations.

Instructions

Help me prioritize these features using the RICE framework. For each feature, help me estimate:

  1. Reach: How many users will this impact per month?
  2. Impact: How much will this impact each user? (Scale: 0.25=minimal, 0.5=low, 1=medium, 2=high, 3=massive)
  3. Confidence: How confident are we in our estimates? (Scale: 0-100%)
  4. Effort: How many person-months will this take to build?

Then calculate the RICE score: (Reach × Impact × Confidence) / Effort

Features to evaluate: [List your features with any context you have]

Best Practices

  • Gather data on current user behavior before estimating Reach
  • Base Impact on user research and pain point severity
  • Be honest about Confidence levels - lower confidence for assumptions
  • Include design, development, and testing time in Effort estimates
  • Revisit estimates after initial discovery work
  • Consider dependencies between features

Example

Input: 5 features (notifications, dark mode, API access, mobile app, analytics dashboard) Output: RICE scores calculated for each, ranked list with reasoning, recommendations on which to prioritize, and suggestions for validating assumptions on low-c...

Read the full file on GitHub · 54 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 54 lines · 33 tokens per session scan A fe6577f032d9

Subscribe to this mod's changes

feature-prioritization-assistant is a skill published in the GitHub repository saski/arnesto (5 stars, last pushed 2d ago), licensed Unlicense. It adds 33 tokens to every session and 488 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to feature-prioritization-assistant, differing in 0 lines, and is treated as a copy.