--- name: roadmap-prioritization-scorer description: "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 recommended build sequence. Use when deciding what to build next, sequencing a backlog, defending priority calls to stakeholders, or reconciling competing requests across workstreams." argument-hint: "[initiatives] [framework]" allowed-tools: ["Read"] --- # Roadmap Prioritization Scorer ## 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](https://docs.anthropic.com/en/docs/claude-code/skills) — markdown with YAML frontmatter at the top. **Installing in Claude Code:** - `~/.claude/skills//SKILL.md` — auto-loads in every session anywhere on your machine (recommended for skills you'll use across multiple projects) - `/.claude/skills//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. 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