Rice

Community

neurofoo

rice

RICE prioritization scoring initiatives by Reach, Impact, Confidence, and Effort. Use for feature prioritization, roadmap planning, or when comparing initiatives objectively.

Overview

Publisher	neurofoo
Repository	`agent-skills`
Skill name	`rice`
Stars	123
Forks	19
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by neurofoo on GitHub. Read the source before you install it.

Installation

Install the Rice AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/neurofoo/agent-skills/tree/main/rice
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/neurofoo/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/rice .claude/skills/rice

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Rice in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Rice on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Rice is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

RICE Prioritization Scoring

Score and rank initiatives using Reach, Impact, Confidence, and Effort to make prioritization decisions more objective.

Instructions

For each initiative, estimate the four RICE factors, calculate the score, and rank them. Be explicit about assumptions behind each estimate.

Output Format

Context What are we prioritizing? What's the time horizon for Reach?

Factor Definitions

Reach: [Define for this context, e.g., "users affected per quarter"]
Impact: [Define for this context, e.g., "effect on conversion rate"]
Effort: [Define unit, e.g., "engineer-weeks"]

Scoring Table

Initiative	Reach	Impact	Confidence	Effort	RICE Score
[Name A]	[#]	[0.25-3]	[%]	[#]	[calculated]
[Name B]	[#]	[0.25-3]	[%]	[#]	[calculated]
[Name C]	[#]	[0.25-3]	[%]	[#]	[calculated]

Ranked Results

[Highest score] — RICE: X
[Second] — RICE: X
[Third] — RICE: X

Detailed Breakdown

For each initiative:

[Initiative Name]

Reach: [X] — [Assumption: how did you estimate this?]
Impact: [X] — [Reasoning for impact level]
Confidence: [X%] — [What would increase confidence?]
Effort: [X] — [What's included in this estimate?]
RICE Score: (R × I × C) / E = [score]

Sensitivity Analysis Which scores would change significantly if assumptions are wrong?

Recommendation Based on the scores and analysis:

[What to prioritize and why, including any caveats]

What RICE Doesn't Capture

Strategic alignment
Dependencies
Team capability gaps
Technical risk

Scoring Guide

Impact Scale

Score	Meaning
3	Massive — core value prop
2	High — significant improvement
1	Medium — noticeable improvement
0.5	Low — minor enhancement
0.25	Minimal — nice to have

Confidence Scale

Score	Meaning
100%	High — have data
80%	Medium — reasonable estimate
50%	Low — mostly guessing

$ARGUMENTS

Frequently asked questions

What does the Rice AI skill do?

RICE prioritization scoring initiatives by Reach, Impact, Confidence, and Effort. Use for feature prioritization, roadmap planning, or when comparing initiatives objectively.

Why use Rice on TypingMind?

Because you install it once and use it with any model. Rice is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Rice in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/neurofoo/agent-skills/tree/main/rice. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Rice?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Rice?

As many as you like. As long as a model supports skills, you can use Rice with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Rice AI skill free?

Yes. It is published on GitHub by neurofoo under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

1password

openclaw

OrganizationPopular

Set up and use 1Password CLI for sign-in, desktop integration, and reading or injecting secrets.

Apple Reminders

List, add, edit, complete, or delete Apple Reminders and reminder lists via remindctl.

Clawhub

Search ClawHub for skills when a requested capability is not already available; install, verify, update, uninstall, publish, or sync skills.

Diagnosing Superpowers

obra

CommunityPopular

Use when a superpowers session went wrong and your human partner wants to know why — repeated work, ignored plans, stumbles, poor results, a skill that didn't fire, "it took too long", "why is it so…

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

RICE Prioritization Scoring

Instructions

Output Format

[Initiative Name]

Scoring Guide

Frequently asked questions

Related AI Skills

Set up your own AI workspace now