Xearno Tools

ACA Subsidy Cliff Checker (2026)

us_aca_subsidy_cliff

Read-only

Where your 2026 marketplace subsidy sits against the restored 400%-of-poverty cliff — and the clawback risk if income crosses it. For 2026 the enhanced ACA premium tax credits have expired, and the pre-2021 structure is back: below 400% of the federal poverty line your premium is capped at a sliding share of income; one dollar above 400% and the subsidy drops to zero. This tool places your household on that curve — your FPL percentage, your expected contribution, your estimated monthly subsidy, and exactly where the cliff falls in dollars. It also flags the 2026 change most people miss: the cap on repaying advance credits was repealed, so if your year-end income lands over 400% you repay every advance dollar with no limit. The decisive input is your FULL-YEAR 2026 MAGI, reconciled at filing — not the estimate you gave at enrollment.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`state`	No	Which state Alaska and Hawaii have higher federal poverty guidelines, which shifts every threshold up.	contiguous
`income`	No	Expected 2026 household income (MAGI) Your best estimate of full-year 2026 household modified AGI — the number the credit is reconciled against at filing, not just what you report at enrollment. A bonus, capital gain, or extra freelance income counts.
`benchmark`	No	Benchmark Silver premium (monthly, for your household) The second-lowest-cost Silver plan (SLCSP) for your household — the plan the subsidy is pegged to. Find yours on healthcare.gov’s plan preview or the KFF subsidy calculator; it varies a lot by age and county. The default is a rough mid-range family figure — replace it for an accurate dollar subsidy.
`expansion`	No	Did your state expand Medicaid? Decides the bottom end. In expansion states, adults under 138% of poverty get Medicaid instead of a marketplace subsidy. In the 10 non-expansion states, adults below 100% FPL fall into the coverage gap — too rich for Medicaid, too poor for a subsidy. *WI covers adults to 100% FPL by waiver.	yes
`household`	No	People in your tax household You, your spouse if filing jointly, and everyone you claim as a dependent — this sets the poverty line the percentage is measured against.

TDQS

A4.7/5.0

Behavior5/5

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

Annotations indicate readOnlyHint=true and openWorldHint=false. The description does not contradict these; it adds significant behavioral context: the decisive input is full-year MAGI reconciled at filing (not enrollment estimate), and the cap on repaying advance credits was repealed, so crossing the cliff means repaying all advances with no limit.

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

Conciseness4/5

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

The description is a single paragraph that front-loads the purpose and then dives into details. It is informative but somewhat lengthy (over 200 words). Each sentence adds value, but some redundancy could be trimmed. Still, it remains clear and well-organized.

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 complexity (5 parameters, no output schema), the description is thorough: it explains the 2026 policy change, the cliff behavior, clawback risk, and each input's role. It covers what the tool returns (subsidy, cliff amount, etc.) adequately for an agent to invoke it correctly.

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

Parameters5/5

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

Schema description coverage is 100%. The description adds substantial meaning beyond the schema: e.g., for 'income' it clarifies MAGI definition and that bonuses/capital gains count; for 'benchmark' it explains SLCSP and where to find it; for 'expansion' it explains Medicaid expansion implications. This adds high value for the agent.

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's purpose: to show where a household's 2026 marketplace subsidy falls relative to the restored 400% FPL cliff, including the clawback risk. It specifies the key outputs (FPL%, contribution, subsidy, cliff dollar amount) and distinguishes itself from other sibling tools which are mostly non-ACA financial calculators.

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

Usage Guidelines4/5

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

The description explains when to use this tool (for 2026 ACA subsidy cliff assessment) and provides critical context about expired enhanced credits and pre-2021 structure. It does not explicitly state when not to use or directly compare to siblings, but the context and sibling list make it clear this is specialized for the ACA cliff.

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

A3.9/5.0

Disambiguation4/5

Each tool targets a distinct niche (e.g., specific country tax rules, loan types, or legal calculations), with detailed descriptions that clarify boundaries. However, the large number of tools (66) could cause some confusion for an agent trying to select the right one for a general query, especially when multiple tools relate to the same country.

Naming Consistency4/5

Tool names follow a mostly predictable pattern: lowercase words separated by underscores, often starting with a country name (e.g., 'uk_stamp_duty_sdlt') or a topic (e.g., 'compound_growth'). There are minor deviations, such as abbreviations ('npv_irr', 'sip') and varying use of verbs, but overall the naming is clear and consistent.

Tool Count3/5

At 66 tools, the server is unusually large and covers an extensive range of financial and legal calculators. While each tool justifies its existence, the count exceeds the typical well-scoped range (3–15), making the server feel bloated. A more modular design might improve coherence.

Completeness4/5

The tool set covers a wide array of domains: personal income taxes, property taxes, loan calculations, investment returns, and specific country regulations. Minor gaps exist (e.g., missing tools for corporate taxes, general retirement planning, or insurance), but the overall coverage is thorough and addresses many niche scenarios that general AI handles poorly.

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