--- name: stakeholder-materiality-prioritizer description: "Applies a structured double-materiality weighting methodology to a list of sustainability topics and stakeholder groups, scoring each topic on stakeholder importance and business impact to produce ranked, matrix-ready input data with quadrant assignments and a documented rationale. Use when preparing a materiality assessment, prioritizing ESG topics for a sustainability report, running a GRI-aligned stakeholder engagement process, or building the underlying data for a materiality matrix." argument-hint: "[topic-list] [stakeholder-groups]" allowed-tools: ["Read"] --- # Stakeholder Materiality Prioritizer ## Purpose Convert a raw list of sustainability topics and stakeholder groups into a defensible, ranked materiality dataset — scoring every topic on stakeholder importance and business impact using a transparent weighting method — so the sustainability team can plot a materiality matrix and justify topic prioritization to auditors, leadership, and GRI reviewers without ad-hoc guesswork. ## When to Use Invoke this skill when the user asks to: - Prioritize or rank sustainability/ESG topics for a materiality assessment - Build the input data or scoring for a materiality matrix - Run a GRI-aligned stakeholder engagement and topic-weighting process - Decide which ESG topics are "material" for a sustainability report - Reconcile conflicting stakeholder priorities into a single ranked list - Apply double materiality (impact + financial) scoring to a topic set ## Inputs Required Before starting, collect: - **Sustainability topics**: The list of topics/issues to assess (e.g., GHG emissions, water use, labor practices, data privacy) - **Stakeholder groups**: The groups being represented (e.g., investors, employees, customers, regulators, communities, suppliers) - **Stakeholder weights**: Relative influence of each group (or leave blank to weight equally) - **Company context**: Sector, size, and geography — needed to calibrate business impact - **Engagement inputs**: Any survey scores, interview notes, or ranking data per group (or note that qualitative estimates should be used) - **Materiality approach**: Single materiality (stakeholder view) or double materiality (impact + financial); default to double - **Reporting framework**: GRI, ESRS/CSRD, SASB, or other alignment target; default to GRI If stakeholder weights or engagement data are missing, weight groups equally, estimate scores from company context, and clearly flag each estimate as an assumption to be validated. ## Instructions ### Step 1: Confirm the Scoring Model Establish the two axes before scoring anything. - **Axis A — Stakeholder Importance (outward view)**: How much each stakeholder group cares about the topic. Scored 1–5 per group, then combined into a weighted average using stakeholder weights. - **Axis B — Business Impact (inward view)**: How much the topic affects the company's ability to create or erode value — risk, cost, revenue, license to operate, resilience. Scored 1–5. - If double materiality is selected, split Axis B into **Impact Materiality** (effect on people/environment) and **Financial Materiality** (effect on enterprise value), each scored 1–5, then take the higher of the two per ESRS logic. Note which driver dominates. - State the 1–5 scale anchors explicitly: 1 = negligible, 2 = minor, 3 = moderate, 4 = significant, 5 = critical. ### Step 2: Score Stakeholder Importance Per Topic For each topic, score every stakeholder group 1–5, then aggregate. - Use provided engagement/survey data where available; otherwise estimate from the group's known priorities and company context, marking estimates as assumptions. - Apply stakeholder weights: Weighted Importance = Σ(group score × group weight) ÷ Σ(weights). If weights are equal, this is a straight average. - Record the highest- and lowest-scoring group per topic to expose divergence. ### Step 3: Score Business Impact Per Topic For each topic, score 1–5 on business impact (or on Impact + Financial if double materiality). - Anchor scores to concrete drivers: regulatory exposure, cost/revenue linkage, operational dependency, reputational risk, and long-term resilience. - For double materiality, note whether Impact or Financial materiality is the binding constraint for each topic. - Calibrate to sector: a topic critical in one industry may be minor in another — use company context to justify each score. ### Step 4: Compute Composite Priority and Rank Combine the two axes into a single ranking. - **Composite Score** = (Weighted Stakeholder Importance + Business Impact) ÷ 2, reported to one decimal. Keep the two axis scores visible so the matrix can be plotted. - Rank all topics from highest to lowest composite score. - Break ties in favor of the topic with the higher Business Impact score (financial/operational risk takes precedence in tie situations). ### Step 5: Assign Materiality Quadrants Map each topic to a matrix quadrant using a 3.0 threshold on each axis. - **Priority / Material** (Importance ≥ 3.0 AND Impact ≥ 3.0): Report-in-full, manage actively. - **Monitor — Stakeholder-Driven** (Importance ≥ 3.0, Impact < 3.0): Watch and disclose; may rise in importance. - **Monitor — Business-Driven** (Importance < 3.0, Impact ≥ 3.0): Manage internally; communicate proactively. - **Low Priority** (both < 3.0): Note only; no active disclosure required. ### Step 6: Flag Divergences and Assumptions Surface where the analysis needs human validation. - List every topic with high stakeholder–business divergence (axis gap ≥ 1.5) — these are the discussion points for the next engagement round. - List all scores derived from estimates rather than data. - Note any topic likely to shift in a re-assessment (emerging regulation, changing sentiment). ## Output Format - **Structure**: A ranked scoring table for all topics, followed by quadrant assignments and a divergence/assumptions section - **Length**: 700–1,100 words plus the tables (scales with topic count) - **Format**: Primary output is a table; supporting analysis in structured bullets - **Sections**: Scoring model summary → Master scoring table (Topic | Weighted Stakeholder Importance | Business Impact | Composite | Rank | Quadrant) → Quadrant groupings → Divergence & assumptions flags → Recommended material topic list for reporting - **Tone**: ESG analyst — methodical, evidence-anchored, audit-ready; every score defensible, no vague qualifiers ## Quality Checklist Before delivering output, verify: - [ ] Every topic provided has a stakeholder importance score, a business impact score, a composite, a rank, and a quadrant - [ ] Stakeholder weights are applied consistently (or equal weighting is explicitly stated) - [ ] All 1–5 scores map to the stated scale anchors — no scores outside 1–5 - [ ] Composite scores are correctly averaged and ranking order matches the scores - [ ] Quadrant assignments correctly follow the 3.0 threshold rule on both axes - [ ] Every estimated (non-data) score is flagged as an assumption to validate ## Notes - The output is decision-support input, not a final materiality determination — the "Priority / Material" list should be reviewed and signed off by stakeholders before publication. - For GRI alignment, the ranked list feeds directly into identifying material topics and their boundaries; for CSRD/ESRS, double-materiality scoring supports the impact-and-financial screening required by the standard. - Divergence flags (axis gap ≥ 1.5) are the most valuable output for engagement planning — they show exactly where stakeholder expectations and business reality disagree. - Re-run this skill each reporting cycle; comparing composite scores year-over-year reveals shifting materiality trends. --- ## 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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