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Roadmap prioritization scorer

Scores and ranks competing product initiatives using a chosen prioritization framework (RICE, ICE, or Value/Effort), returning a ranked table with per-initiative scores, transparent rationale, tie-break logic, and a…

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Purpose

Turn a messy list of competing feature requests and initiatives into a defensible, ranked roadmap by scoring each one against a consistent framework — producing per-initiative scores, transparent rationale, and a recommended build sequence a PM can bring straight into a planning meeting.

When to Use

Invoke this skill when the user asks to:

  • Decide what to build next or sequence a backlog
  • Score initiatives with RICE, ICE, or Value vs. Effort
  • Reconcile competing requests coming from sales, support, leadership, and users
  • Defend or justify a prioritization decision to stakeholders
  • Re-rank a roadmap after new data, deadlines, or capacity changes
  • Compare two or three initiatives that are all "top priority"

Inputs Required

Before starting, collect:

  • Initiative list: The features, epics, or bets to rank — name plus a 1–2 sentence description of each
  • Framework: RICE, ICE, or Value/Effort (default to RICE if unspecified)
  • Reach data (per initiative): Estimated users or accounts affected per time period, or best-guess proxy
  • Business goal: The primary outcome this quarter (revenue, retention, activation, cost reduction) so "Impact" is scored against something real
  • Effort estimates: Rough sizing per initiative — person-weeks, T-shirt size, or story points
  • Constraints: Hard deadlines, dependencies, compliance/legal must-dos, or capacity ceilings
  • Confidence notes: Which estimates are data-backed vs. gut-feel (used to set the Confidence factor honestly)

If reach, effort, or confidence data is partial, score with reasonable estimates, flag each assumption inline, and mark low-confidence scores explicitly rather than inflating them.

Instructions

Step 1: Confirm the Framework and Its Scoring Rules

Lock the scoring model before touching any initiative.

  • RICE: Score = (Reach × Impact × Confidence) ÷ Effort
  • Reach: number of people/accounts affected per period (e.g., per quarter)
  • Impact: 3 = massive, 2 = high, 1 = medium, 0.5 = low, 0.25 = minimal
  • Confidence: 100% = high, 80% = medium, 50% = low (penalizes guesswork)
  • Effort: total person-months (or person-weeks — keep the unit constant)
  • ICE: Score = (Impact × Confidence × Ease) ÷ each rated 1–10, then averaged or multiplied — state which. Faster, lower-rigor, good for early-stage lists.
  • Value/Effort: Plot each initiative on a 2×2 (High/Low Value × High/Low Effort) and prioritize Quick Wins → Big Bets → Fill-ins → avoid Money Pits.

State the exact formula and rating scale being used so every score is reproducible.

Step 2: Score Each Initiative Component by Component

For every initiative, assign each factor with a one-line justification — never a bare number.

  • Tie Impact to the stated business goal, not to generic "user delight"
  • Set Confidence based on the confidence notes: data-backed → high, informed estimate → medium, speculation → low
  • Keep the Effort unit identical across all initiatives (mixing weeks and months invalidates the ranking)
  • Where an input is missing, use a stated proxy and mark it as an assumption

Step 3: Calculate and Rank

  • Compute the framework score for each initiative
  • Sort descending into a ranked table
  • Round scores to a readable precision (whole numbers or one decimal), but preserve raw values for tie-breaks

Step 4: Apply Tie-Breaks and Override Logic

Pure scores don't capture everything — layer in judgment transparently.

  • Ties (within ~10% score): break by strategic alignment to the primary goal, then by lower effort
  • Hard overrides: compliance/legal must-dos, contractual deadlines, and unblocking dependencies get sequenced ahead of raw score — flag each override explicitly with the reason
  • Dependency ordering: if a high-ranked item depends on a lower-ranked one, note the required sequence shift
  • Sandbagging check: flag any initiative that ranks high only because of an inflated Reach or optimistic Confidence

Step 5: Recommend a Build Sequence

Translate the ranking into an actionable order.

  • Group into Now / Next / Later (or Sprint 1 / Sprint 2 / Backlog)
  • Note capacity: how far down the list realistic capacity reaches given the effort estimates
  • Call out the single item most likely to be contested and pre-arm the PM with the one-line defense

Output Format

  • Structure: Framework declaration → ranked scoring table → per-initiative rationale → tie-break/override notes → recommended build sequence
  • Length: 700–1,100 words plus the table
  • Format: A ranked table (rank, initiative, each factor, final score) followed by structured bullets
  • Sections: Framework & Formula → Ranked Scoring Table → Scoring Rationale → Overrides & Tie-Breaks → Recommended Sequence (Now/Next/Later) → Contested Call to Watch
  • Tone: Decisive product-lead — quantitative, transparent about assumptions, willing to make a call and defend it

Quality Checklist

Before delivering output, verify:

  • [ ] Every initiative provided has a complete score with all framework factors filled in
  • [ ] The scoring formula and rating scale are stated explicitly and applied identically to every initiative
  • [ ] Effort is expressed in one consistent unit across all initiatives
  • [ ] Every assumption or proxy used for missing data is flagged inline
  • [ ] All hard overrides (compliance, deadlines, dependencies) are called out with reasons, not buried in the score
  • [ ] The output ends with a concrete Now/Next/Later sequence, not just a raw ranked list

Notes

  • RICE is best when you have real reach and effort data; ICE is faster for early-stage or exploratory lists; Value/Effort is best for a lightweight stakeholder-friendly visual
  • The Confidence factor is the most-skipped and most-valuable input — honest low-confidence scores prevent shiny-but-unproven bets from jumping the queue
  • A prioritization is only as trustworthy as its inputs; when reach or effort is a guess, say so rather than manufacturing false precision
  • If two initiatives keep trading ranks under small assumption changes, that's a signal to run a quick discovery spike before committing, not to force a decision

How to use this skill

This file is a Claude Code skill in Anthropic's standard format — markdown with YAML frontmatter at the top.

Installing in Claude Code:

  • ~/.claude/skills/<folder-name>/SKILL.md — auto-loads in every session anywhere on your machine (recommended for skills you'll use across multiple projects)
  • <your-project>/.claude/skills/<folder-name>/SKILL.md — auto-loads only when working in that project (recommended for project-specific skills)

Restart Claude Code or open a new session to register.

Using in Claude.ai, ChatGPT, Gemini, or other AI tools:

  1. Drag this file into a new chat, or copy and paste its contents
  2. Send your task or request as your next message — the AI will apply the skill where it fits

For Claude Code skill details: https://docs.anthropic.com/en/docs/claude-code/skills