mlp-tax
Server Details
Deterministic MLP tax computation engine. 6 tools: basis projection, estate planning, sell vs hold comparison, MLP vs ETF tax analysis, distribution stress test, and MLP reference data. Returns IRS-cited calculations for K-1 basis tracking, §751 recapture, and §199A QBI.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Usage analytics
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Tool Definition Quality
Average 4.5/5 across 6 of 6 tools scored.
Each tool has a clearly distinct purpose with explicit use-case guidance and 'Don't use for' notes. Tools like k1_basis_compute (single-year) and k1_basis_multi_year (multi-year) are unambiguously separated, and mlp_projection vs mlp_sell_vs_hold target different decision points.
All tool names follow a consistent lowercase_with_underscores convention and use prefixes to indicate domain ('k1_basis_' for Schedule K-1 basis tools, 'mlp_' for broader MLP tools). The naming pattern is predictable and descriptive.
With 6 tools, the server is well-scoped for MLP tax analysis. Each tool covers a distinct workflow (single-year basis, multi-year basis, projection, sell-vs-hold, estate planning, reference info) without unnecessary overlap.
The tool set covers the core MLP tax lifecycle: basis computation from K-1s, long-term projection, sell-vs-hold analysis, and estate planning. The inclusion of a reference info tool rounds out the surface. Gaps like multi-lot or state analysis are explicitly noted and within scope boundaries.
Available Tools
6 toolsk1_basis_computeARead-onlyIdempotentInspect
Computes adjusted partner basis from a single year of Schedule K-1 data using the IRS Partner's Basis Worksheet methodology (Lines 1-14), per IRC §705 (basis computation), §722 (initial basis), §731(a)(1) (gain on distribution exceeding basis), §733 (basis reduction), §752 (liability share allocation), §704(d) (loss limitation and suspended-loss carryforward), and §199A (QBI deduction). Returns the ending adjusted basis, every worksheet line value, any §731 gain triggered when distributions exceed basis, and §704(d) suspended losses carried forward.
Use when: User holds direct MLP units (EPD, ET, MPLX, WES, PAA, NRP, USAC, SUN, or similar publicly traded midstream partnerships) and has structured K-1 box values for one tax year — Box 1 ordinary income, Box 19A cash distributions, Item K liability change, optionally Box 5 interest income, Box 11 §179 deduction, Box 13W §199A QBI amount. Single tax year, single lot.
Don't use for: 1099-DIV ETFs (AMLP, MLPX, AMZA — these use RIC structure, no K-1, different tax regime — use a standard cost-basis calculator instead). Multi-year basis carryforward across consecutive K-1s — use k1_basis_multi_year. General partnership interests outside publicly traded MLPs (different §1402 self-employment treatment).
Limitations: Single tax year only — for multi-year basis tracking with §731 gain detection across years, use k1_basis_multi_year. Single-lot only — for multi-lot allocation and optimal sell ordering, see lucasandersen.ai. Federal-level only — does not include state basis adjustments.
Maintained by Lucas Andersen, MS Finance, with direct positions in major midstream MLPs. Methodology auditable at lucasandersen.ai/methodology.
| Name | Required | Description | Default |
|---|---|---|---|
| box1 | Yes | K-1 Box 1: ordinary business income (loss) | |
| box2 | No | K-1 Box 2: net rental income | |
| box5 | No | K-1 Box 5: interest income | |
| box11 | No | K-1 Box 11: §179 / other deductions | |
| units | Yes | ||
| box13w | No | K-1 Box 13W: §199A QBI amount | |
| box19a | Yes | K-1 Box 19A: cash distributions | |
| ticker | Yes | ||
| prior_basis | Yes | Beginning-of-year adjusted basis in USD | |
| tax_bracket | No | ||
| liability_decrease | No | §752(b) liability decrease in USD | |
| liability_increase | No | §752(a) liability increase in USD |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is well-covered. The description adds useful behavioral details: returns ending basis, worksheet line values, §731 gain detection, and §704(d) suspended losses. It also mentions auditable methodology. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is structured with clear sections: purpose, legal references, output summary, usage conditions, limitations, and maintenance info. It front-loads the core purpose. While somewhat lengthy, every sentence adds value, and the structure aids quick parsing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (12 parameters, no output schema), the description thoroughly explains the tool's inputs, outputs (ending basis, line values, gains, losses), and limitations (single-year, single-lot, federal only). It compensates for the missing output schema by detailing return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 75% schema coverage, the description adds meaning by contextualizing which K-1 boxes (Box 1, Box 19A, Item K, optional Box 5, Box 11, Box 13W) are used. However, tax_bracket and liability_increase/decrease are not explicitly linked back to the description. Still, it provides good guidance beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes adjusted partner basis using IRS methodology (Lines 1-14) and IRC sections. It specifies the use case (MLP units, structured K-1 box values) and explicitly distinguishes from siblings like k1_basis_multi_year.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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, indicating when the tool is appropriate (direct MLP units, single year) and when it's not (1099-DIV ETFs, multi-year). It also names alternative tools like k1_basis_multi_year and standard cost-basis calculators.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
k1_basis_multi_yearARead-onlyIdempotentInspect
Computes a running adjusted partner basis across multiple years of Schedule K-1 data, per IRC §705 (basis computation), §731(a)(1) (gain on distributions exceeding basis), §751(a) (accumulated ordinary recapture), §752 (liability share allocation across years), §704(d) (suspended-loss carryforward), and §1014(a) (step-up if death today). Returns year-by-year basis trajectory, accumulated §751 recapture estimate, projected zero-basis year, §1014 step-up value if death today, and the broker-basis gap — the dollar amount by which a typical 1099-B understates true IRS-adjusted basis.
Use when: User holds a direct MLP position (EPD, ET, MPLX, WES, PAA, NRP, USAC, SUN) across multiple consecutive tax years, has K-1s for those years, and wants to track adjusted basis year over year, identify the zero-basis year, quantify the gap between broker-reported basis and true IRS basis, or project §1014 step-up value if death occurred today.
Don't use for: Single-year basis worksheet from one K-1 — use k1_basis_compute. Long-horizon forward projection from default assumptions when no actual K-1s are in hand — use mlp_projection. 1099-DIV ETFs (AMLP, MLPX, AMZA — RIC structure, no K-1, no basis-erosion mechanism; use a standard cost-basis calculator). Multi-position portfolio basis tracking — this tool handles one position per call.
Limitations: Single position, single lot — for multi-lot or multi-position basis tracking with optimal sell ordering, see lucasandersen.ai. Federal-level only — does not include state-level basis adjustments. Accumulated §751 recapture is estimated across years; actual depends on the partnership's hot-asset disposition schedule and any year-specific §751(b) events.
Maintained by Lucas Andersen, MS Finance, with direct positions in major midstream MLPs. Methodology auditable at lucasandersen.ai/methodology.
| Name | Required | Description | Default |
|---|---|---|---|
| units | Yes | ||
| ticker | Yes | ||
| k1_years | Yes | Array of annual K-1 data, one per year held (max 50) | |
| tax_bracket | No | ||
| purchase_year | No | ||
| purchase_price | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint. The description adds behavioral context: federal-level only, single position/lot, no state adjustments, recapture estimated, and methodology auditable. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, usage guidelines, limitations, maintenance info). It is relatively long but every sentence adds value. Could be slightly more concise, but the complexity of the tool justifies the length. Front-loaded with main purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the description enumerates all expected outputs (year-by-year basis trajectory, accumulated §751 recapture, zero-basis year, §1014 step-up, broker-basis gap). It also covers limitations, use cases, and maintainer info, making it fully adequate for an AI agent to understand what the tool returns and when to use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 17%, so the description should compensate. While it lists required inputs (ticker, units, purchase_price, k1_years) and explains what k1_years contains (array of annual K-1 data with box1, box19a, etc.), it does not provide detailed semantics for each schema property beyond usage context. The description helps but does not fully compensate for low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states it computes a running adjusted partner basis across multiple years of K-1 data, lists specific outputs (basis trajectory, recapture, zero-basis year, step-up, broker-basis gap), and distinguishes from siblings like k1_basis_compute (single-year) and mlp_projection (forward projection without actual K-1s).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Clearly specifies when to use (direct MLP position with multiple consecutive K-1s) and when not to use (single-year, forward projections, non-K-1 ETFs, multi-position portfolios), with explicit alternatives for each exclusion. Also notes limitations (single position/lot, federal-only, estimated recapture).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mlp_estate_planningARead-onlyIdempotentInspect
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.
Maintained by Lucas Andersen, MS Finance, with direct positions in major midstream MLPs. Methodology auditable at lucasandersen.ai/methodology.
| Name | Required | Description | Default |
|---|---|---|---|
| positions | Yes | Array of MLP positions to analyze (max 20) | |
| tax_bracket | No | ||
| beneficiaries | No | Number of beneficiaries (default 1, max 20) | |
| community_property | No | Whether positions are in a community property state (doubles step-up) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true and idempotentHint=true, so the description is consistent. It adds value by detailing output (deferred tax, recapture eliminated, inheritance splits), limitations (federal-only, §751 estimate), and maintained by. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is lengthy (over 300 words) and includes maintenance info and methodology links that may be extraneous. It is well-structured but front-loads key info. Could be more concise without losing clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of estate planning and no output schema, the description covers functionality, limitations, alternative tools, and scope (direct units only). It is complete enough for an agent to select and invoke correctly, though adding expected output structure would improve it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 75% with descriptions for positions, beneficiaries, community_property. The description does not add parameter-level details beyond the schema. Baseline 3 is appropriate as the description provides minimal extra semantic value for parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes §1014 stepped-up basis and estate-planning analysis for direct MLP positions. It distinguishes from siblings by listing alternative tools (e.g., mlp_projection, mlp_sell_vs_hold) and explicitly excludes trust-based strategies and ETFs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use scenarios (quantify step-up benefit, compare hold-to-death vs sell, community property, per-beneficiary splits) and when-not-to-use (trusts, single-position projections, RIC ETFs) with sibling names. This gives clear guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mlp_infoARead-onlyIdempotentInspect
Returns reference data for a supported MLP ticker — current cash distribution per unit, distribution growth CAGR, default return-of-capital percentage, distribution coverage ratio, K-1 entity count, operating-state count, and last-verified date.
Use when: User wants to look up baseline characteristics of an MLP before modeling — e.g., comparing distribution coverage across partnerships, checking how many K-1 entities a holding generates for tax-prep complexity, or seeing the operating-state count for state-tax filing-burden estimation.
Don't use for: Tax computation. Use mlp_projection (long-horizon modeling), mlp_estate_planning (estate analysis), mlp_sell_vs_hold (break-even sell price), or k1_basis_compute / k1_basis_multi_year (computing basis from actual K-1 data).
Note: This tool returns reference data only — no IRC citations apply, no methodology disclosure attached. For computation, use the modeling tools above.
Maintained by Lucas Andersen, MS Finance.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint and idempotentHint, covering safety and idempotency. The description adds that it returns reference data only, with no IRC citations or methodology disclosure, and notes maintenance by Lucas Andersen. This goes beyond annotations by explaining the nature of the output.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear first sentence, followed by usage guidance sections and a maintenance note. It is somewhat lengthy but every sentence adds value, and it is front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple lookup tool with one parameter and no output schema, the description fully covers what the tool does, when to use it, and its limitations (reference data only). The list of returned fields compensates for the missing output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It mentions 'ticker' in context and the enum defines allowed values, but no additional detail on format or meaning beyond what the schema provides. This is adequate but not exceptional.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description begins with 'Returns reference data for a supported MLP ticker' and lists specific fields, clearly stating the tool's purpose. It distinguishes from siblings by listing alternative tools and what not to use it for.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit 'Use when' and 'Don't use for' sections provide clear context and alternatives. The description lists specific use cases and explicitly names sibling tools for different scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mlp_projectionARead-onlyIdempotentInspect
Computes a multi-year tax projection for a publicly traded MLP position, applying the IRS Partner's Basis Worksheet methodology (Lines 1-14) per IRC §705 (basis computation), §731(a) (distributions exceeding basis), §733 (basis reduction), §751 (hot asset recapture), §752 (liability allocation), §1014 (stepped-up basis at death), and §199A (QBI deduction). Returns year-by-year basis erosion, §751 accumulation, annual federal tax, terminal FMV, §1014 step-up value at death, and the break-even sell price.
Use when: User holds direct units of a midstream MLP (EPD, ET, MPLX, WES, PAA, NRP, USAC, SUN) and wants to model long-term tax outcomes — when basis reaches zero, total tax paid over the hold horizon, deferred tax eliminated by §1014 step-up at death, or the unit price at which selling matches holding through inheritance. Single position, single lot.
Don't use for: 1099-DIV ETFs (AMLP, MLPX, AMZA — these use RIC structure, pay corporate-level tax, and issue 1099-DIV instead of K-1; use a standard cost-basis calculator instead). Multi-position estate analysis — use mlp_estate_planning. Computing basis from actual K-1 data the user has in hand — use k1_basis_compute (single year) or k1_basis_multi_year.
Limitations: Single position, single lot — for multi-position portfolios and per-lot optimal sell ordering, see lucasandersen.ai. Federal-level only — does not include state-level basis adjustments or state estate tax. §751 recapture is estimated from default ROC assumptions; actual recapture depends on the partnership's hot-asset disposition schedule.
Maintained by Lucas Andersen, MS Finance, with direct positions in major midstream MLPs. Methodology auditable at lucasandersen.ai/methodology.
| Name | Required | Description | Default |
|---|---|---|---|
| units | Yes | Number of MLP units held | |
| years | No | Projection horizon in years (1-50, default 20) | |
| ticker | Yes | MLP ticker symbol | |
| tax_bracket | No | Federal marginal rate as decimal, e.g. 0.32 (default 0.32) | |
| purchase_price | No | Purchase price per unit in USD (optional — defaults to reasonable estimate) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and idempotentHint=true. The description adds significant behavioral context: limitations (single position, single lot, federal-only, §751 estimate) and methodology note, which go beyond annotations. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is lengthy but well-structured: first sentence states core purpose, followed by use cases, exclusions, limitations, and a methodology note. It is front-loaded but could be more concise. Every sentence earns its place, but length slightly reduces conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity, annotations, and schema coverage, the description is comprehensive. It explains what it returns (year-by-year basis erosion, tax, etc.), limitations, and alternative tools. Without an output schema, the description covers return values adequately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with basic descriptions. The description adds meaning beyond schema by explaining the overall output (basis erosion, §751 accumulation, etc.) and defaults (purchase price estimate). However, schema already covers parameters, so a slight premium for methodological context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes a multi-year tax projection for an MLP position, applying IRS methodology. It specifies the resource (MLP position) and verb (computes projection), and distinguishes itself from sibling tools by listing what not to use and providing alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (direct MLP units, modeling long-term tax outcomes) and when not to use (1099-DIV ETFs, multi-position estate, computing from actual K-1 data). Provides specific alternative tools (standard cost-basis calculator, mlp_estate_planning, k1_basis_compute).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mlp_sell_vs_holdARead-onlyIdempotentInspect
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.
Maintained by Lucas Andersen, MS Finance, with direct positions in major midstream MLPs. Methodology auditable at lucasandersen.ai/methodology.
| Name | Required | Description | Default |
|---|---|---|---|
| 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 |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate read-only and idempotent behavior. The description adds value by disclosing limitations (single position/single lot, break-even price assumes tax bracket persistence, §751 recapture estimated from defaults) and methodology transparency (maintainer identity, auditable at website). No contradiction with annotations found.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is somewhat lengthy (multiple paragraphs) but every sentence adds value for a complex financial tool. Front-loaded with core purpose and tax references; limitations and maintenance notes are placed at the end. Structure is logical and efficient for the domain.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 7 parameters, no output schema, and complex tax logic, the description covers the essential purpose, use cases, alternatives, and limitations. It explains the return value (break-even sell price). Missing parameter descriptions are a gap, but the overall context is sufficient for an agent to select and understand the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is low (29%). Only ticker and years_held have descriptions in schema; the tool description does not add parameter-level details for the 5 undocumented parameters. It compensates slightly by explaining the conceptual role of certain inputs (e.g., tax brackets), but not enough to fully bridge the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool compares selling an MLP position today vs holding until death, calculates a break-even sell price, and references specific IRC sections. It distinguishes from sibling tools (mlp_estate_planning, mlp_projection) by stating what the tool does not do, ensuring clear differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Clear 'Use when' and 'Don't use for' sections provide explicit guidance. The description lists appropriate scenarios (time-sensitive sell decisions, retirement planning) and exclusions (multi-position portfolio, RIC-structured ETFs), with direct references to alternative tools (mlp_estate_planning, mlp_projection).
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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