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Random number generator

random_number_generator

Generate cryptographically random integers in a range, optionally unique and sorted. Runs on smart-tools.xyz.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
maxYesHighest value (inclusive)
minYesLowest value (inclusive)
countNoHow many numbers to generate (default 1, max 10000)
localeNoLanguage for the source_url link (default en)
sortedNoSort ascending (default false)
uniqueNoNo repeats (default false)

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations present, the description carries the full burden for behavioral disclosure. It adds the important context that the numbers are cryptographically random, and implies no side effects. However, it does not mention potential edge cases (e.g., min > max) or output format, leaving some transparency gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that conveys the core purpose and key optional behaviors. The trailing 'Runs on smart-tools.xyz' adds little value for an AI agent and could be considered minor fluff, but overall it is concise.

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 computational tool with a fully documented schema, the description plus schema is fairly complete. It does not describe the return value format, but for a random number generator the output is intuitive (a number or array of numbers) and no output schema is provided. The description is sufficient for basic invocation.

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 coverage is 100%, so the schema already documents all parameters. The description adds semantic color by mentioning 'range' (mapping to min/max) and 'unique and sorted' (mapping to boolean flags), but does not elaborate beyond what the schema says. Baseline 3 is appropriate.

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 ('Generate') and identifies the exact resource ('cryptographically random integers in a range'), while also mentioning optional uniqueness and sorting. This clearly distinguishes it from sibling tools like password_generator or uuid_generator.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives such as password_generator or uuid_generator. It only states the tool's function, leaving the agent to infer usage context from the tool name and sibling list.

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

B3.3/5.0
Disambiguation3/5

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.

Naming Consistency4/5

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.

Tool Count2/5

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.

Completeness4/5

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.

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