PaycheckHours calculators

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

With no annotations, the description carries the full burden and does well: it discloses the 14-day input cap, that shifts past midnight are handled, how breaks are treated, and the exact overtime rule sets (federal 40h/1.5x vs. state daily rules). It does not state whether this is a pure computation with no side effects, nor any rounding/precision behavior for currency.

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?

Two sentences, each densely packed with operative facts (limits, formats, break handling, overtime variants, optional pay output), with the core computation front-loaded. No filler or restatement of the title.

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 4-parameter calculator with no output schema, the description covers inputs, constraints and the two categories of result (overtime split and gross pay). What it omits is the shape of the response — e.g. per-day vs. per-week totals and how the overtime figures are returned — which an agent would need to use the result.

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 100%, so the baseline is 3, and the description earns an extra point by explaining the 7-days-per-workweek ordering constraint and that the weekly threshold defaults to 40 when no state is supplied. The state enum's daily-rule semantics are also restated in prose rather than only in the field description.

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 uses a specific verb ('adds up a time card') with explicit scope limits (up to 14 days, 7 per workweek), break subtraction and midnight handling, plus overtime and gross-pay computation. It is clearly distinct from convert_decimal_hours and split_tip_pool, but it never addresses the overtime_pay sibling, which overlaps on the overtime calculation, so differentiation is incomplete.

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?

Usage conditions are concrete: state rules apply only for CA/AK/NV/CO, the weekly threshold applies when no state is given, and gross pay is only produced when an hourly rate is supplied. There is no explicit exclusion or routing statement versus overtime_pay, which keeps it out of 5 territory.

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

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

No annotations are provided, so the description must carry the behavioral burden. It adequately describes the computation and gives an example, implying a safe pure calculation, but it does not explicitly state that the tool is side-effect free, how invalid inputs are handled, or whether the two optional parameters are mutually exclusive.

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?

Two short sentences with zero waste: the conversion behavior is front-loaded and the example immediately anchors the H:MM-to-decimal mapping. Every sentence earns its place.

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 two-parameter calculator with a fully described schema and no output schema, the description is nearly complete. The 'or' phrasing signals the mutually exclusive direction, though it could more explicitly say to provide exactly one of the two optional parameters.

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%, so the schema already documents both parameters with examples. The description's example '7:45 is 7.75 hours' reinforces meaning but largely repeats what the schema descriptions already provide, so the baseline of 3 is appropriate.

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 uses a specific verb, 'Converts', and names the exact resources: hours/minutes (H:MM) and decimal hours. It also states that conversion works in both directions, so the purpose is clear, but it does not explicitly differentiate this tool from the sibling tools.

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 bidirectional phrasing 'or' implies that one format should be supplied to get the other, which is useful context. However, it gives no explicit guidance on when to choose this tool over siblings such as calculate_time_card or overtime_pay, and no exclusions are stated.

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

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

With no annotations, the description must carry the behavioral burden. It usefully discloses defaults the schema does not (multiplier 1.5, double time 2x) and grounds them in the US federal rule, but says nothing about permissions, limits, or whether the result is a total or a breakdown.

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?

Two tightly written sentences: the core computation first, then the multiplier semantics. No filler, and the most decision-relevant detail (the default) is surfaced immediately.

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?

No annotations and no output schema mean the description is the only source of truth, yet it never says what the return value looks like (a single number, a component breakdown, currency formatting). For a five-parameter calculation tool this leaves a meaningful gap.

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?

At 0% schema coverage the description has to explain all five parameters, and it effectively does: hourly rate and hours of each category are implied, double_time_hours is defined as 2x, and overtime_multiplier gets a default value of 1.5 with rationale. It stops short of defining boundaries such as whether regular_hours is capped at 40.

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 names a specific computation ('regular, overtime and double-time pay from an hourly rate and hours'), so the agent knows exactly what the tool produces. It does not, however, differentiate itself from the sibling calculate_time_card, which likely overlaps in scope.

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?

There is no statement of when to use this tool versus calculate_time_card or any other sibling, nor any prerequisites or exclusions. Usage is only inferable from the names of the inputs, leaving the agent to guess between overlapping pay-calculation tools.

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

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

With no annotations, the description carries the full burden. It does disclose a real behavioral trait beyond the schema: rounding to the cent with shares guaranteed to sum exactly to the total. But it says nothing about edge-case handling (zero-hour participants, zero total hours), whether the call is a pure computation with no side effects, or what the result looks like.

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?

One sentence, front-loaded with the operation and followed immediately by the allocation and rounding guarantee. Nothing is wasted and nothing competes for attention.

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?

There is no output schema, so the description should ideally sketch the return shape (per-person amounts, ordering, whether the total is echoed). It covers the allocation rule well but leaves the response contract and edge cases unaddressed for a two-parameter computational 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 50% — only total_tips carries a description ('US dollars'), while the people array and its hours field are undocumented. The description partially compensates by establishing that hours are the proportional weight, but it does not clarify units, allowed ranges, or duplicate-name handling.

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 gives a specific verb and resource ('Splits a tip pool by hours worked') plus the allocation rule, which is enough to distinguish it from the payroll-calculation siblings (calculate_time_card, convert_decimal_hours, overtime_pay). It stops short of naming those siblings explicitly, but the operation is unambiguous.

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?

There is no guidance on when to use this versus the sibling payroll tools, and no stated preconditions — nothing about whether hours may be zero, whether the array may be empty, or what happens if total hours sum to zero. The agent must infer all invocation conditions.

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