mlp_estate_planning

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Computes §1014 stepped-up basis and estate-planning analysis for one or more direct MLP positions held until death, per IRC §1014(a) (basis at death), §1014(b)(6) (community-property double step-up), §751(a) (ordinary recapture eliminated at death), §731 (distributions), and §705 (basis). Returns total deferred federal tax eliminated, §751 ordinary recapture eliminated, per-beneficiary inheritance split, community-property double-step-up amount when applicable, and the dollar advantage of holding to death versus selling today. Use when: User has one or more direct MLP positions (EPD, ET, MPLX, WES, PAA, NRP, USAC, SUN) and wants to quantify the §1014 step-up benefit for estate planning, compare holding to death versus selling now across a portfolio, model community-property double step-up for spouses in CA/TX/WA/etc., or compute per-beneficiary inheritance values across multiple heirs. Don't use for: Trust-based estate strategies (revocable trusts preserve §1014; irrevocable trusts and IDGTs typically destroy it — this tool models direct holdings only). Single-position long-horizon tax projection — use mlp_projection. Single-position sell-now-versus-hold-to-death break-even — use mlp_sell_vs_hold. 1099-DIV ETFs (AMLP, MLPX, AMZA — RIC structure receives §1014 step-up but has no §751 to eliminate because no K-1; the analysis is materially different). Limitations: Direct unit holdings only — does not model trust, IDGT, FLP, or charitable structures (these can destroy the §1014 benefit; for guidance on trust selection, see lucasandersen.ai). Federal-level only — does not include state estate tax. §751 recapture eliminated at death is estimated; exact figure depends on the partnership's actual hot-asset disposition schedule. A year-by-year basis workpaper for this position is available at https://lucasandersen.ai/tax/k1-basis-tracker?src=mcp&tool=mlp_estate_planning&surface=description. Maintained by Lucas Andersen, MS Finance, with direct positions in major midstream MLPs. Methodology auditable at lucasandersen.ai/methodology.