calc.engineer

tip calculator

tip_calculator

Calculate tip and split a restaurant bill among multiple people. Given a bill amount, tip percentage, and number of diners, returns the tip amount, total with tip, per-person share, and effective tip percentage. Supports rounding up to the nearest whole number for convenience. Defaults to 18% tip for 1 person. Currency-agnostic — works with any monetary unit.

Input Schema

TableJSON Schema

Name	Required	Description
`split`	No	Number of people splitting the bill. Defaults to 1 (no split).
`tip_pct`	No	Tip percentage. Common values: 15 (standard), 18 (good), 20 (great), 25 (excellent). Defaults to 18%.
`round_up`	No	Round the total up to the nearest whole number. Defaults to false.
`bill_amount`	Yes	Total bill amount before tip (any currency).

Output Schema

TableJSON Schema

Name	Required	Description
`total`	Yes	Bill plus tip.
`tip_amount`	Yes	Tip amount.
`per_person_tip`	Yes	Each person's share of the tip.
`per_person_total`	Yes	Each person's total including their share of the bill and tip.
`effective_tip_pct`	Yes	Actual tip percentage after rounding (if round_up is true, may differ from input).

TDQS

A4.8/5.0

Behavior5/5

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

No annotations are provided, so the description carries the full burden. It discloses key behaviors: rounding up support, default tip and split, currency-agnostic nature, and the computed outputs (tip, total, per-person share, effective percentage). This gives the agent a complete picture of what the tool does and its side-effect-free calculation nature.

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 three sentences long, with the main purpose front-loaded, followed by key details. Every sentence adds information without redundancy or fluff.

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 tool's moderate complexity (4 parameters, 1 required) and the existence of an output schema, the description covers inputs, outputs, defaults, edge cases (rounding), and domain context (currency-agnostic). It is fully adequate for agent understanding.

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 coverage is 100%, and the description enriches the parameters beyond the schema by explaining defaults ('18% tip for 1 person'), the rounding feature, and the meaning of tip percentage values. This adds 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: calculating tip and splitting a restaurant bill. It specifies the verb (calculate, split), resource (restaurant bill), and distinct outcomes (tip amount, total, per-person share). Sibling tools are all different calculators, so no ambiguity.

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 frames the tool for restaurant bill scenarios, but does not explicitly state when to use it vs alternatives or when not to use it. Since it's the only tip calculator among siblings, the context is clear enough.

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

Despite 89 tools, each has a clearly distinct purpose with detailed descriptions that often reference related tools. Overlap exists (e.g., multiple LoRa/RF tools), but the descriptions are sufficient to distinguish them. Some confusion possible among similar-sounding tools like attenuator_pi and attenuator_tee, but the descriptions explicitly compare them.

Naming Consistency4/5

Consistent underscore-separated lowercase naming. Most tools follow a verb_noun pattern (e.g., capacitor_charge, wire_gauge) or noun_noun (power_cost). Minor inconsistencies such as 'bmi_calculator' vs 'solar_sizing' but overall predictable.

Tool Count2/5

89 tools is far too many for a single MCP server. This scope is more appropriate for multiple specialized servers. The sheer number will slow agent selection and increase cognitive load, reducing coherence.

Completeness3/5

Covers many domains (RF, solar, PCB, networking, math, etc.) but lacks depth in some areas (e.g., no three-phase power, no airflow calculations). Some domains have comprehensive coverage (LoRa/Meshtastic), but others feel incomplete for the tool count.

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