MLP Tax Computation Engine

mlp_sell_vs_hold

Read-onlyIdempotent

Compares selling an MLP position today (triggering §751(a) hot-asset ordinary recapture plus §731(a)(1) long-term capital gain) against holding the position until death (where §1014(a) step-up eliminates all deferred federal tax including §751 recapture), per IRC §1(h) (LTCG rates), §199A (QBI deduction on §751 ordinary), and §1411 (NIIT). Returns the break-even sell price — the unit price above which selling today produces more after-tax wealth than holding through inheritance.

Use when: User holds a direct MLP position (EPD, ET, MPLX, WES, PAA, NRP, USAC, SUN), is approaching a sell decision, and wants a single break-even threshold to compare against the current market price. Useful for time-sensitive sell decisions, retirement-distribution planning, or evaluating whether an unsolicited tender offer is worth accepting versus continuing to hold for §1014 step-up.

Don't use for: Multi-position portfolio sell-ordering — this tool models a single position. For estate-planning analysis across multiple positions and beneficiaries, use mlp_estate_planning. For long-horizon basis-erosion modeling without a sell decision in view, use mlp_projection. 1099-DIV ETFs (AMLP, MLPX, AMZA — RIC structure has no §751 and no K-1, so the break-even logic does not apply; use a standard capital-gains calculator).

Limitations: Single position, single lot — for portfolio-wide optimal sell ordering across multiple positions and lots, see lucasandersen.ai. Break-even price assumes the supplied tax bracket persists through the hold horizon. §751 recapture on the sell side is estimated from default ROC assumptions; actual hot-asset recapture depends on the partnership's 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_sell_vs_hold&surface=description.

Maintained by Lucas Andersen, MS Finance, with direct positions in major midstream MLPs. Methodology auditable at lucasandersen.ai/methodology.

Input Schema

TableJSON Schema

Name	Required	Description
`units`	Yes
`ticker`	Yes
`years_held`	No	Years the position has been held (default 10)
`tax_bracket`	No
`purchase_price`	No
`years_to_project`	No	Years to project the hold scenario (default 10)
`community_property`	No

TDQS

A4.5/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description carries less burden. It adds valuable context: the tool assumes constant tax brackets, single position/lot, and that §751 recapture is estimated from default ROC assumptions. It also links to a basis workpaper for further detail.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with sections: purpose, formula/example, use cases, exclusions, limitations, and attribution. Every sentence adds value, and the most critical information (purpose, break-even calculation) is front-loaded. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (7 parameters, no output schema), the description is highly complete. It explains the output (break-even sell price), underlying assumptions, limitations, and provides external links for methodology and basis tracking. An agent has sufficient context to decide when to invoke this tool and what to expect.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is low (29%), with only two parameters having descriptions. The description does not individually explain each parameter but compensates somewhat by explaining the tool's logic and required inputs (ticker, units). The mention of 'default ROC assumptions' hints at parameter usage but does not fully specify the meaning of all seven parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool compares selling an MLP position today versus holding until death, producing a break-even sell price. It distinguishes from siblings by explicitly naming mlp_estate_planning and mlp_projection as alternatives for different use cases.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit 'Use when' and 'Don't use for' sections, listing specific scenarios (e.g., time-sensitive sell decisions, retirement-distribution planning) and exclusions (e.g., multi-position portfolio, RIC/ETF structures). It also references sibling tools for those alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.4/5.0

Disambiguation5/5

Each tool targets a very specific and distinct use case: single-year basis, multi-year basis, long-term projection, estate planning, sell-vs-hold decision, and reference data lookup. The descriptions clearly state when to use each and (crucially) when not to, making selection unambiguous.

Naming Consistency4/5

Tool names mostly follow the pattern of domain prefix followed by the specific operation (e.g., k1_basis_compute, mlp_projection, mlp_sell_vs_hold). The naming is clear, though 'mlp_estate_planning' is a full phrase rather than verb_noun, which is a minor deviation from an otherwise strong pattern.

Tool Count5/5

With 6 tools covering basic reference, single-year basis, multi-year basis, projection, estate planning, and sell-vs-hold decision, the count is well-scoped for the domain. Each tool serves a clear purpose, and there is no bloat or missing critical functionality for the stated MLP tax and estate analysis use cases.

Completeness5/5

The tool set provides complete coverage of the MLP tax and estate planning lifecycle: retrieving reference data, computing single-year and multi-year basis, projecting future tax scenarios, comparing sell vs. hold, and analyzing estate step-up benefits. All major decision points and IRC sections are addressed, leaving no obvious gaps for a direct MLP holder.

Resources

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