neqsim-asset-value-npv-screening

name	neqsim-asset-value-npv-screening
version	0.1.0
description	Educational discounted-cash-flow (DCF) asset-value screening that builds a year-by-year net cash flow from revenue, OPEX, and a CAPEX schedule and returns NPV, IRR, and payback with a simple flat tax. USE WHEN: a task needs a public, screening-level NPV/IRR/payback before detailed NeqSim field-development economics or qualified commercial review.
last_verified	2026-06-24
requires	{"python_packages":[],"java_packages":[],"env":[],"network":[]}

Asset Value (NPV) Screening

Use this skill for a quick, public discounted-cash-flow (DCF) screening of an asset. Given a year-by-year revenue series, an OPEX series (or a flat value), and a CAPEX schedule (or a single year-0 spend), it computes net cash flow, discounts it to a net present value (NPV), and estimates IRR and payback. It is a transparent placeholder that should guide users toward the validated NeqSim field-development DCF utilities and the NeqSim MCP runFieldEconomics workflow.

When to Use

• When a user wants a first-pass NPV / IRR / payback for a concept.
• When an agent has a production-and-price revenue profile plus a cost screen.
• When examples must run without confidential fiscal terms or licensed tools.

Inputs

• annual_revenue_musd: sequence of annual revenues in million USD (one per year).
• annual_opex_musd: a flat OPEX or a per-year sequence in million USD.
• capex_schedule_musd: a single year-0 spend or a per-year sequence in million USD.
• discount_rate_fraction: annual discount rate (default 0.08).
• tax_rate_fraction: flat tax on positive operating profit (default 0.0).

Outputs

• net_cash_flow_musd: per-year revenue - OPEX - tax - CAPEX.
• discounted_cash_flow_musd: per-year discounted cash flow.
• cumulative_cash_flow_musd: running (undiscounted) cumulative cash flow.
• npv_musd: net present value.
• irr_fraction: internal rate of return (or None if not identifiable).
• payback_year / discounted_payback_year: first year cumulative turns non-negative.
• total_capex_musd / total_revenue_musd: roll-up totals.
• value_warning: ok (NPV>0), watch (NPV=0), or high (NPV<0).
• neqsim_available: whether the optional NeqSim package is importable.
• assumptions: public assumptions and required follow-up.

Engineering Method

For each year, operating profit is revenue - OPEX; tax is tax_rate * max(0, operating profit); net cash flow is operating profit - tax - CAPEX. NPV discounts each net cash flow at year-end: NPV = sum(CF_t / (1 + r)^t) for t = 1..N. IRR is the rate that zeroes NPV, found by bisection over a wide bracket (returns None when there is no sign change). Payback is the first year cumulative cash flow becomes non-negative.

This skill models no inflation, depreciation, uplift, ring-fencing, financing, or working capital. It is a placeholder that must be replaced by validated NeqSim economics for any quantitative or commercial use.

Python Usage Pattern

from asset_value_npv_screening import AssetValueModel

model = AssetValueModel()
result = model.evaluate(
    annual_revenue_musd=[0.0, 300.0, 320.0, 280.0, 230.0, 180.0],
    annual_opex_musd=40.0,
    capex_schedule_musd=[600.0, 200.0, 0.0, 0.0, 0.0, 0.0],
    discount_rate_fraction=0.08,
    tax_rate_fraction=0.78,
)

print(result.npv_musd)
print(result.irr_fraction)
print(result.payback_year)
print(result.value_warning)

Validated NeqSim Path

This screening is a placeholder. For real asset economics use:

• The field-development DCF utilities in neqsim.process.util.fielddevelopment for cash-flow modelling, fiscal regimes, and uncertainty (see the neqsim-field-economics skill).
• The NeqSim MCP runFieldEconomics tool for an orchestrated NPV/IRR evaluation with tax regimes (Norwegian NCS, UK, generic) and Monte Carlo sensitivity.

Escalation

Escalate any high verdict, any negative NPV, and any commercial decision to a validated NeqSim economics evaluation and qualified commercial review.

Validation Checklist

• Inputs are validated and within stated ranges.
• Examples use public data only.
• Screening assumptions are stated explicitly.
• Limitations are respected.
• Quantitative use is escalated to validated NeqSim models.

Common Mistakes

Symptom	Cause	Fix
Unrealistic result	Inputs outside the screening range	Keep inputs within the stated bounds
Misused for design	Screening output taken as final	Escalate to validated NeqSim models

Limitations

• Educational screening only; not a validated design method.
• No confidential data or proprietary methods are included.
• Escalate any quantitative or design use to validated NeqSim workflows.

References

• NeqSim repository: https://github.com/equinor/neqsim
• NeqSim Skills Guide: https://github.com/equinor/neqsim/blob/master/docs/integration/skills_guide.md