Xearno Tools

Freelance vs Employee: the True-Equivalence Rate

us_freelance_vs_employee

Read-only

The 1099 rate that truly replaces a W-2 salary — solved from taxes, benefits, and billable reality, not a folk multiplier. Rules of thumb ("charge 1.5× your salary hourly") hide what actually changes when you go independent: you pay both halves of Social Security and Medicare, buy the whole health premium instead of the employee share, self-fund the 401(k) match, and bill far fewer hours than you work. One thing runs the other way — the §199A QBI deduction (made permanent in 2025) shelters about 20% of profit from income tax, and models routinely forget it. This tool solves for the 1099 gross at which your net-of-everything genuinely matches the W-2 job, then divides by the hours that realistically bill. All 2026 parameters verified on IRS primary sources; benefit defaults from the KFF 2025 employer survey.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`filing`	No	Filing status	single
`salary`	No	The W-2 salary to match Annual gross salary of the job you have or are comparing against.
`matchPct`	No	Employer 401(k) match (%) Percent of salary your employer contributes. Default: the 2025 Vanguard average (4.7%). The freelancer self-funds this to stay even (deductible via a solo 401(k)).
`weeksWorked`	No	Working weeks per year After vacation, holidays, and sick time — which no longer come paid. A W-2 job with ~23 paid days off works ≈47 weeks but is paid for 52.
`hoursPerWeek`	No	Hours worked per week (freelance)
`utilizationPct`	No	Billable share of worked hours (%) The hidden lever. Sales, admin, invoicing, and bench time don’t bill — professional-services benchmark is ~66%; solo practices vary widely.
`employeeHealthCost`	No	Your share of health premium as an employee (annual) What comes out of your paycheck for coverage. Default: KFF 2025 average worker contribution for single coverage.
`freelanceHealthCost`	No	Full health premium as a freelancer (annual) What you would pay for comparable coverage on your own (marketplace or otherwise). Default: KFF 2025 average single premium. Family coverage runs ~$27,000. Deductible against income tax (not SE tax).

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, so the tool is a pure calculation. The description adds behavioral context: it solves for net equality, details tax components (Social Security, Medicare, QBI deduction), benefit defaults, and warns about common omissions. This adds value beyond annotations without contradiction.

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 a single, well-structured paragraph that front-loads the main purpose. Every sentence adds value: explaining the tool, why it's needed, key variables, and data sources. It is concise for the complexity without being verbose.

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

Completeness4/5

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

Given 8 parameters and no output schema, the description explains the model well, including hidden levers. It hints at the output (1099 gross rate divided by billable hours). However, it could more explicitly describe the output format or breakdown, but the overall completeness is high.

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?

The input schema has 100% coverage with each parameter described. The tool description adds some context (e.g., default matchPct from Vanguard, utilizationPct benchmark) but does not significantly enhance understanding beyond the schema. Baseline 3 is appropriate for high schema coverage.

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 computes the 1099 equivalent rate that truly matches a W-2 salary, differentiating it from simple multipliers. The title reinforces this purpose. It is specific about the resource (freelance vs employee compensation) and the verb (solves/compares), distinguishing it from sibling tools that cover other financial calculations.

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 implicitly guides when to use the tool: when comparing freelance vs employee compensation to find the true equivalence, contrasting it with 'rules of thumb'. It does not explicitly state when not to use, but the sibling list includes many other specific tools, so the context is clear. It also mentions data sources for 2026 parameters, adding confidence.

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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