Mjrtl Pm Agent Skills Idea Prioritization

Idea Prioritization (ICE Framework)

Goal

Ingest an idea description and current state, score it on Impact, Confidence, and Ease, and compute the ICE Score = Impact x Confidence x Ease to propose an execution priority. All evaluations must follow explicit criteria and rely only on stated evidence; no inference or guesswork.

When to use

• To quickly order an idea backlog and select items for exploration and experiments
• When you have at least some explicit evidence (interviews/data/tests) and a rough team effort estimate
• Before drafting experiment plans for a leaf opportunity in an Opportunity Solution Tree

Input

• Idea title and description: goal, target metric, scope, and working hypothesis
• Idea analysis and current state: data/user/market/test evidence, execution hypothesis, risks, and effort estimate
• Optional:
  • Target metric and expected change rate (%) or range
  • Estimated effort (person-weeks)

Output

• Format: Markdown (.md)
• Location: initiatives/[initiative]/solutions/
• Filename: ice-[YYYY-MM-DD]-[slugified-idea-title].md

Scoring model

For the full scoring model details, see references/ice-scoring-model.md.

Quick reference

• Impact: Map expected metric change (%) to a 0-10 scale
• Ease: Map estimated effort (person-weeks) to a 10-1 scale (less effort = higher ease)
• Confidence: Sum weighted evidence contributions with group caps
• ICE Score = Impact x Confidence x Ease

Priority buckets

Process

1. Input validation: Verify target metric, expected change (%), evidence text, and estimated effort (person-weeks). If missing, ask clarifying questions.
2. Impact scoring: Map % change to the Impact table; if missing, apply default Impact 2.
3. Ease scoring: Map person-weeks to the Ease table; if uncertain, use conservative lower ease.
4. Evidence extraction and classification: Count only impact-related evidence from the input. Tally per type and apply group caps.
5. Confidence calculation: Sum per-type contributions, apply group caps, compute final Confidence (0-10).
6. ICE computation: Compute ICE = I x C x E; assign priority bucket.
7. Report generation: Include score table, calculation rationale, cap applications, risks/assumptions, and recommended next steps.

Output format

# ICE Evaluation -- [Idea Title]

## Overview
- **Idea:** [Title]
- **One-line Summary:** [Brief description]
- **Target Metric:** [Metric name]
- **Assumptions/Scope:** [Key assumptions]

## Score Summary
- **Impact:** [I] (basis: [expected % change or default rule])
- **Ease:** [E] (basis: [person-weeks])
- **Confidence:** [C] (see details in references/ice-scoring-model.md)

## ICE Calculation
- ICE = [I] x [C] x [E] = **[Score]**
- **Priority Guidance:** [Bucket label]

## Input Summary
- **Expected Metric Change:** [value/none -> default 1.5% applied]
- **Estimated Effort (person-weeks):** [value/uncertain]
- **Evidence Excerpts:**
  - [Excerpt 1; classified as: user/market/test/...]
  - [Excerpt 2; classified as: ...]

## Risks / Assumptions
- [Key risk]
- [Key uncertainty]

## Recommended Next Steps
- [Tests/data collection/research/prototype]
- Confidence Improvement Plan: [Which evidence to strengthen]

## Notes
- ICE is a fast comparison/sorting tool; final decisions must also consider strategy, market, and resources.

Guardrails

• Do not invent or infer evidence or over-credit weak signals
• Exclude evidence not directly tied to Impact from Confidence
• When uncertain, apply conservative caps and document in "Risks/Assumptions"
• Prevent duplicate counting of the same source/content

Customization (team tuning)

• Adjust Impact bands to your target metric sensitivity
• Adjust Ease bands to team speed/role mix
• Extend evidence keywords to your domain language, while preserving the "explicit evidence only" rule
• Recalibrate bucket thresholds per quarterly capacity/roadmap density

Follow the writing standards in _shared/writing-standards.md for all outputs.

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