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True Hourly Wage (Gig & Side Hustle)

true_hourly_wage
Read-only

What a gig actually pays per hour — after vehicle costs, waiting time, and self-employment tax. Turns gross gig or side-hustle earnings into the real hourly wage: counting every hour worked (including waiting and driving between jobs), the full per-mile cost of the vehicle (not just gas), and the tax that no employer is withholding. Then compares the result to minimum wage — and is honest when the answer is "stay home."

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
grossNoGross earnings / week What the app(s) paid you, before anything.
hoursNoTotal hours / week Include waiting, driving between jobs, and returning empty — research finds unpaid "deadhead" time is about a third of gig working time.
milesNoMiles driven / week All of them, including empty miles. 0 if the hustle has no vehicle.
taxPctNoTax on profit (%) US self-employment tax alone is ~14% of profit; add your income-tax bracket for the fully-taxed number. Set 0 to see pre-tax.
minWageNoLocal minimum wage The benchmark an employer would legally have to beat. US federal is $7.25; many states/cities are $15+.
costPerMileNoVehicle cost / mile Gas alone is ~$0.12–0.18/mi. The IRS all-in rate (fuel + maintenance + depreciation + insurance) is ~$0.70/mi. Most drivers’ true cost is $0.25–0.45.

TDQS

A4/5.0
Behavior4/5

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

The description adds context beyond annotations by detailing what costs are included (vehicle cost, waiting time, self-employment tax) and stating it compares to minimum wage and is 'honest when the answer is stay home.' Annotations indicate read-only, which is consistent.

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 concise and front-loaded with the main purpose, followed by clear enumerations of included factors. Every sentence adds value without redundancy.

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 high schema coverage and no output schema, the description adequately explains the input factors and implies the output (comparison to minimum wage). It is complete for a calculator tool, though it could explicitly mention the output type.

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 100%, so the baseline is 3. The tool description reiterates concepts but does not add new parameter-specific meaning beyond what the schema provides.

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 function: calculating the true hourly wage of a gig after accounting for vehicle costs, waiting time, and self-employment tax. It uses specific verbs and resources, and distinguishes itself from sibling financial calculators by focusing on gig/side-hustle earnings.

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

Usage Guidelines3/5

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

The description implies usage when assessing gig earnings, but does not explicitly state when to use this tool versus alternatives or provide 'when not to use' guidance. It lacks reference to sibling tools for comparison.

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.

Resources