Automated summary
Scores and ranks initiatives using the RICE formula, with explicit assumptions and a sensitivity analysis.
Strengths
- Standardized output with a scoring table and ranked results
- Context-specific factor definitions and impact/confidence scales
- Detailed assumption breakdown and sensitivity analysis
- Clearly states what RICE does not capture
Limitations
- Reach, impact, confidence, and effort estimates remain subjective
- Output quality depends on the data the user provides
- Does not directly incorporate strategic alignment, dependencies, or technical risk
Use when comparing features or roadmap items with rough quantitative estimates to make prioritization more objective.
Avoid when strategic dependencies or qualitative factors dominate, or when reach and effort estimates are unreliable.
Security analysis
SafeThe skill is a pure instructional template for RICE prioritization scoring. It declares no tools, executes no commands, and contains no destructive, exfiltrating, or obfuscated instructions. It only provides a structured framework and output format for analytical reasoning.
No concerns found
How this analysis is madeExamples
Priorise ces trois fonctionnalités pour le prochain trimestre avec RICE : notifications push, import CSV et tableau de bord analytics. Suppose une portée trimestrielle et explique chaque estimation.Applique RICE à ces idées de roadmap et donne-moi un classement avec les hypothèses, une analyse de sensibilité et une recommandation.Aide-moi à arbitrer ce backlog avec le scoring RICE. Voici les initiatives et mes estimations de reach, impact, confiance et effort : ...name: rice description: RICE prioritization scoring initiatives by Reach, Impact, Confidence, and Effort. Use for feature prioritization, roadmap planning, or when comparing initiatives objectively. user-invocable: true
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
From the file to a first result
The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.
View the source and supporting filesThis download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.
1. Download the file
Download SKILL.mdFrom the root of a test project, save the file as .skill-downloads/rice-prioritization-scoring-mu26hb18/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.
Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.
mkdir -p '.skill-downloads/rice-prioritization-scoring-mu26hb18' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/rice-prioritization-scoring-mu26hb18/download' --output '.skill-downloads/rice-prioritization-scoring-mu26hb18/SKILL.md.part' && mv '.skill-downloads/rice-prioritization-scoring-mu26hb18/SKILL.md.part' '.skill-downloads/rice-prioritization-scoring-mu26hb18/SKILL.md'2. Check prerequisites
Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.
No recognized prerequisites section in this file. This does not mean it is self-contained: libraries, tools and access requirements may be mentioned elsewhere in the content or source repository.
The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.
3. Load the skill
After inspection, copy the complete folder into your project using one of the commands below, then open a new tool session. The command stops if a folder with the same name already exists: compare the files before replacing it.
Claude Code
test -f '.skill-downloads/rice-prioritization-scoring-mu26hb18/SKILL.md' && test -s '.skill-downloads/rice-prioritization-scoring-mu26hb18/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/rice' && cp -R '.skill-downloads/rice-prioritization-scoring-mu26hb18' '.claude/skills/rice'OpenSkills
OpenSkills must already be installed. The local install/read procedure is checked with OpenSkills 1.5.0, which requires Node.js ≥ 20.6.0. Catalog slugs are not resolved automatically.
Official OpenSkills installationopenskills install './.skill-downloads/rice-prioritization-scoring-mu26hb18'openskills read 'rice-prioritization-scoring-mu26hb18'Reading should display the installed file content and its base directory. It does not run the skill or install its dependencies.
For an agent that reads AGENTS.md, then sync the index. This command changes AGENTS.md: review the diff before using it.
openskills syncManual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.
4. Try a first task
Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:
Read .skill-downloads/rice-prioritization-scoring-mu26hb18/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.
PDF Reader
Productivity
Read and extract text from PDF files, including documents, reports, contracts, and spreadsheets. Works with local files, URLs, and WhatsApp attachments. Use whenever PDF content is needed, even if not explicitly requested.
Discord Messaging Workflows
Productivity
Use the message tool to send, edit, and moderate Discord messages with interactive components.
Interactive Verdict Preview
Productivity
Generate an interactive HTML preview of keep/drop verdicts for maintainer review, then process the pasted feedback JSON.