SupplyChainEsgSkill

---
name: SupplyChainEsgSkill
description: >
  Produce supply chain ESG digests by combining supplier scores, emission data, and policy templates.
version: 1.0.1
visibility: organization
tags:
  - supply-chain
  - esg
  - sustainability
entrypoint:
  command: generate_esg_brief
  label: Assemble supply chain ESG brief
---

## When Claude should load this skill
- Run ahead of ESG steering committees, board updates, or supplier risk reviews requiring sustainability context.
- Use when teams must merge scorecards, emissions inventory, and remediation plans into one deliverable.

## Core workflow
1. Review `instructions/esg-briefing.md` for scoring thresholds, disclosure requirements, and stakeholder messaging.
2. Execute `python scripts/esg_report.py` to emit `ESG_SUMMARY` and `SUPPLIER_MATRIX` with high-risk vendor signals.
3. Populate `templates/esg-actions.md` with prioritized interventions, timelines, and procurement owners.

## Linked resources
- `data/supplier_scores.csv` — Third-party or internal supplier ESG ratings with category breakdowns.
- `data/emission_inventory.csv` — Scope 1-3 emissions data by supplier, commodity, and reporting period.
- `instructions/esg-briefing.md` — Narrative structure, compliance notes, and disclosure language.
- `templates/esg-actions.md` — Action plan framework for presenting commitments and mitigations.
- `docs/regional-regulations.md` — Optional reference of jurisdiction-specific ESG reporting rules.

import pandas as pd

suppliers = pd.read_csv("data/supplier_scores.csv")
emissions = pd.read_csv("data/emission_inventory.csv")

top_risk = suppliers.sort_values("risk_score", ascending=False).head(5)
combined = suppliers.merge(emissions, on="supplier_id", how="left")

summary = {
    "high_risk_suppliers": top_risk[["supplier_name", "risk_score", "region"]].to_dict("records"),
    "total_emission": float(emissions["co2e"].sum()),
}

print("ESG_SUMMARY=", summary)
print("SUPPLIER_MATRIX=", combined.to_dict("records")[:10])