bmr_calculatorBasal metabolic rate (Mifflin–St Jeor) and daily calories (TDEE = BMR × activity). Runs on smart-tools.xyz.
| Name | Required | Description | Default |
|---|---|---|---|
| age | Yes | Age in years | |
| sex | Yes | Biological sex | |
| locale | No | Language for the source_url link (default en) | |
| activity | No | Activity multiplier: 1.2 sedentary, 1.375 light, 1.55 moderate, 1.725 active, 1.9 very active (default 1.2) | |
| height_cm | Yes | Height in cm | |
| weight_kg | Yes | Weight in kg |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility. It does not disclose any behavioral traits such as output format, side effects, or whether it requires network access. The only additional detail is 'Runs on smart-tools.xyz', which is a hosting note and not behaviorally informative. The formula and method are disclosed, but that is more about computation logic than tool behavior.
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 first sentence is concise and informative, but the second sentence ('Runs on smart-tools.xyz') is filler that does not help an agent select or invoke the tool. It is short overall, but the wasted sentence prevents a higher score.
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 is a straightforward calculator with full parameter documentation in the schema. The description explains the formulas and distinguishes it from siblings. The output is inferable (numeric BMR and TDEE values), so the lack of an output schema is not a significant gap. The only minor omission is explicit mention of return value structure.
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?
The input schema provides descriptions for all six parameters (100% coverage), so the baseline is 3. The description itself does not add any parameter-specific semantic information beyond what the schema already contains, nor does it explain the relationships between parameters (e.g., activity multiplier default).
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 computes Basal Metabolic Rate (BMR) using the Mifflin-St Jeor equation and Total Daily Energy Expenditure (TDEE) as BMR × activity. This is specific and distinguishes it from sibling calculators like BMI or body fat calculators.
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: when BMR/TDEE calculations are needed. However, it gives no explicit guidance on when to use it over alternatives (e.g., BMI calculator) or when not to use it. The context is clear but there are no exclusions or alternative tool references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools are clearly distinct, but there are notable overlaps. 'hash_generator' and 'file_hash' effectively do the same thing (SHA hashing of text), and several CSV/TSV converters (csv_to_json, csv_to_sql, table_to_csv, markdown_table) have similar input handling, though outputs differ. The sheer number of converters is clear, but these near-duplicates create some ambiguity.
Names follow a generally consistent pattern: lowercase with underscores, often ending in 'converter', 'calculator', or 'generator'. A few names like 'base64', 'lorem_ipsum', and 'transliteration' deviate from the suffix pattern, but the naming style is uniform and predictable overall.
With 73 tools, this server is far over the typical well-scoped range. While the broad utility-toolkit purpose might justify a larger set, 73 is unwieldy and pushes well into 'too many' territory, making it harder for an agent to select the right tool efficiently.
The server covers a remarkably wide range of common utilities: unit conversions, calculators, text transformations, development helpers (JSON, regex, JWT, subnet), and generators. Minor gaps exist (e.g., currency converter, time zone converter), but for a general-purpose toolkit, it is largely comprehensive.