brine_calculatorBrine Calculator (Salt Ratio by Weight) — Calculate salt and sugar for wet or dry brines by weight: enter water volume or meat weight and a salt percentage to get exact grams and a strength chart.
| Name | Required | Description | Default |
|---|---|---|---|
| mode | Yes | ||
| saltPct | Yes | ||
| sugarPct | Yes | ||
| waterVolumeL | Yes | ||
| meatWeightGrams | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It states the calculation output (exact grams and strength chart) but does not mention side effects, limitations, error handling, or the fact that this is a pure read-only computation. However, being a calculator, the behavior is largely implied by the description's focus on computation.
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?
The description is a single front-loaded sentence with no redundant content. It efficiently communicates the tool's purpose, inputs, and outputs in a compact form.
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?
The tool has no annotations, no output schema, and five required parameters, yet the description does not clarify that all parameters are required, how mode alters input requirements, or what the return structure looks like. It mentions some inputs and an output chart but leaves significant gaps for correct invocation, especially regarding parameter combinations and constraints.
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 0%, so the description must compensate. It references water volume, meat weight, salt percentage, sugar (implied), and wet/dry modes, but does not explicitly name all five parameters or explain the relationship between mode and which inputs are required. The phrase 'enter water volume or meat weight' hints at mode-dependent usage but leaves ambiguity about the exact parameter schema.
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 clearly states the tool calculates salt and sugar for wet or dry brines by weight, with a specific verb ('Calculate') and resource ('brine'). It distinguishes itself from sibling calculators by naming the unique domain and the specific output (exact grams and strength chart).
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 description implies usage context (brine preparation by weight) but does not explicitly state when to use this tool versus alternative calculators or provide exclusions. It mentions entering water volume or meat weight, which gives a hint about mode-dependent input, but there is no direct comparison to siblings or guidance on mode selection.
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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Every tool follows the same <topic>_calculator pattern with lowercase snake_case, making the naming highly predictable and consistent. Even acronyms and numbers fit the pattern, so there is no mixing of conventions.
122 tools is an extreme number for a single MCP server, far exceeding the 50+ threshold for a severe mismatch. The tools span unrelated domains like AI costs, pet food, concrete, pizza dough, and turkey cooking, creating an unfocused kitchen-sink surface that overwhelms an agent's selection process.
The set covers many common calculator categories such as finance, construction, health, and AI costs, but several staple calculators are missing (e.g., BMI, tip, discount, simple interest, currency conversion). The AI cost cluster is over-saturated while other everyday calculations are absent, leaving minor but noticeable gaps.