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One Rep Max (1RM) Calculator

one_rep_max_calculator

One Rep Max (1RM) Calculator — Estimate your one-rep max from any set using the Epley and Brzycki formulas, then read a full percentage-of-1RM table to set training loads for every lift.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repsYes
weightYes
formulaYes

TDQS

A4/5.0
Behavior4/5

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

With no annotations provided, the description carries the transparency burden. It discloses the key behavioral elements: it estimates 1RM using two named formulas and produces a full percentage-of-1RM table. It does not mention limitations like high-rep formula validity or weight units, but the core behavior and output type are clearly stated.

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 sentence that front-loads the purpose and packs every clause with meaningful information: formula names and output table. There is no filler or redundant content.

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?

For a simple calculator with no output schema, the description adequately explains what the tool does and what the result provides (a percentage-of-1RM table). It doesn't specify the exact return structure or edge cases, but the essential information for selection and invocation is present.

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 0%, so the description must compensate. It does imply the meaning of the parameters: 'any set' indicates weight and reps input, and 'Epley and Brzycki formulas' maps to the formula parameter. However, it does not explicitly define units, constraints, or the impact of choosing one formula over the other, leaving some ambiguity.

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 uses a specific verb ('Estimate') with a clear resource ('one-rep max') and additionally names the Epley and Brzycki formulas and the percentage-of-1RM table output. This clearly distinguishes it from sibling calculators by focusing on strength-training 1RM estimation.

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 phrase 'from any set' implies the common use case of estimating 1RM from a performed set, but there is no explicit guidance about when to choose this tool over alternatives, no exclusions, and no mention of prerequisite knowledge. The context is enough for basic selection but lacks direct comparator guidance.

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

B3.1/5.0
Disambiguation2/5

Many calculators occupy overlapping conceptual spaces, such as 'ai_roi_calculator' vs 'ai_automation_payback_calculator' and 'llm_self_host_vs_api_calculator' vs 'ai_build_vs_buy_calculator'. The boundaries between debt payoff, savings goal, and drawdown tools are also fuzzy, making it easy for an agent to select the wrong tool despite detailed descriptions.

Naming Consistency5/5

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.

Tool Count1/5

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.

Completeness3/5

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.

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