modeling-carbon-credit-economics
Builds carbon credit models with offset generation analysis, verification costs, and market pricing dynamics for carbon-linked investments. Use when modeling carbon credits, analyzing offset economics, or evaluating carbon market exposure.
Best use case
modeling-carbon-credit-economics is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Builds carbon credit models with offset generation analysis, verification costs, and market pricing dynamics for carbon-linked investments. Use when modeling carbon credits, analyzing offset economics, or evaluating carbon market exposure.
Teams using modeling-carbon-credit-economics should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/modeling-carbon-credit-economics/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How modeling-carbon-credit-economics Compares
| Feature / Agent | modeling-carbon-credit-economics | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Builds carbon credit models with offset generation analysis, verification costs, and market pricing dynamics for carbon-linked investments. Use when modeling carbon credits, analyzing offset economics, or evaluating carbon market exposure.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Modeling Carbon Credit Economics ## When To Use - Evaluating a carbon offset project (forestry, DAC, methane capture, cookstoves, etc.) as an investment or revenue stream - Modeling credit generation volumes and timing for a specific project methodology - Pricing carbon credits across compliance and voluntary markets - Analyzing the cost stack from origination through verification and retirement - Stress-testing carbon-linked investment returns under varying regulatory and market scenarios - Comparing project types or registries on an economics basis ## Inputs To Gather - **Project type and methodology** — REDD+, ARR, avoided methane, direct air capture, improved cookstoves, etc. - **Registry and standard** — Verra (VCS), Gold Standard, ACR, CAR, or compliance programs (EU ETS, CCA, RGGI) [VERIFY registry-specific issuance rules] - **Baseline and additionality documentation** — project design document (PDD), baseline emissions scenario - **Land/asset parameters** — hectares, capacity, sequestration or avoidance rates per unit - **Credit issuance schedule** — crediting period length, buffer pool contribution, expected vintage distribution - **Cost inputs** — project development, MRV (monitoring, reporting, verification), registry fees, brokerage, legal - **Market pricing data** — spot and forward prices by credit type, vintage, and co-benefit attributes - **Regulatory context** — applicable compliance market rules, Article 6 corresponding adjustment status [VERIFY jurisdiction-specific compliance eligibility] - **Buyer/offtake terms** — fixed-price ERPAs, spot sales, streaming arrangements, volume commitments ## Workflow 1. **Classify the credit type and market** - Determine whether credits are compliance-grade or voluntary-only - Identify the applicable methodology version and crediting period - Note any co-benefit certifications (CCB, SD VISta) that affect pricing premiums 2. **Model gross credit generation** - Build a year-by-year issuance schedule based on sequestration/avoidance curves - Apply methodology-specific decay, leakage, and permanence discount factors - Deduct buffer pool contributions (typically 10–40% for nature-based projects) [VERIFY buffer pool % by methodology] - Output: net annual credits available for sale (tCO₂e/year) 3. **Build the cost stack** - **Development costs** — feasibility, PDD preparation, legal structuring, community engagement - **MRV cycle costs** — remote sensing, field verification, third-party auditor fees (typically every 3–5 years) - **Registry and transaction fees** — issuance fees, transfer fees, retirement fees - **Ongoing management** — project monitoring, community benefit-sharing, insurance - **Brokerage and marketing** — intermediary commissions (5–15% on voluntary market sales) - Calculate all-in cost per credit ($/tCO₂e) on a levelized basis over the crediting period 4. **Model revenue and pricing dynamics** - Set base-case pricing by credit category (nature-based removal, avoidance, tech-based removal) - Apply vintage discounting — older vintages typically trade at a discount - Incorporate co-benefit premiums where applicable - Model offtake structure: percentage sold forward via ERPAs vs. spot exposure - Build price scenarios: bear (oversupply / integrity concerns), base, bull (Article 6 demand / corporate net-zero mandates) 5. **Calculate investment returns** - Project-level IRR and NPV at each price scenario - Cash flow waterfall: development → first issuance → steady-state → crediting period expiry - Breakeven credit price (the $/tCO₂e needed to achieve target return) - Payback period under base-case assumptions 6. **Run sensitivity and risk analysis** - Key variables to stress: credit price (±30%), issuance volume (±20%), verification cost escalation, buffer pool invalidation events - Regulatory risk: methodology invalidation, Article 6 corresponding adjustment requirements, registry policy changes [VERIFY current Article 6 implementation status] - Permanence risk: reversal events (fire, disease, land-use change) and insurance adequacy - Counterparty risk: ERPA buyer credit quality, volume shortfall penalties 7. **Document assumptions and deliver model** - Create an assumptions register with source citations for every input - Flag all [VERIFY] items for client or specialist confirmation - Provide scenario comparison summary table ## Output The deliverable is a financial model (spreadsheet or structured output) containing: - **Issuance schedule** — annual net credits by vintage over the crediting period - **Cost model** — itemized and levelized cost per credit - **Revenue model** — scenario-based revenue by year with offtake mix - **Returns summary** — IRR, NPV, breakeven price, payback period per scenario - **Sensitivity tables** — tornado chart inputs showing return sensitivity to key variables - **Assumptions register** — every input sourced and flagged where verification is needed - **Risk matrix** — regulatory, permanence, market, and counterparty risks with mitigation notes ## Quality Checks - Verify that buffer pool deductions match the specific registry/methodology rules — do not use generic percentages without confirmation - Confirm crediting period length aligns with the methodology version (e.g., VCS 7-year renewable vs. 10-year fixed) [VERIFY] - Ensure cost-per-credit calculation includes all MRV cycles, not just the first verification - Cross-check pricing assumptions against recent transaction data (e.g., Ecosystem Marketplace, S&P Platts assessments) - Validate that IRR calculations properly reflect the J-curve: development spend precedes first issuance by 2–4 years - Confirm that compliance-grade claims are backed by actual registry eligibility — do not assume voluntary credits qualify for compliance use - Check that co-benefit premium assumptions are supported by observable market data, not aspirational pricing