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random_number

Generate random integers in a range, one or many. Pure CPU, instant.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "min": "<min>"
    },
    "name": "random_number"
  }
}

Input Schema

NameRequiredDescriptionDefault
maxNoMaximum
minYesMinimum
countNoHow many

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. Changed4 schema fields changed
    • addedInput schema / properties / count
      Added value: +{
      +  "description": "How many",
      +  "type": "integer"
      +}
    • addedInput schema / properties / max
      Added value: +{
      +  "description": "Maximum",
      +  "type": "integer"
      +}
    • addedInput schema / properties / min
      Added value: +{
      +  "description": "Minimum",
      +  "type": "integer"
      +}
    • addedInput schema / required
      Added value: +[
      +  "min"
      +]
  4. Added

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and 'Pure CPU, instant' usefully signals no network calls, no side effects, and low latency. However, it omits whether the generator is cryptographically secure (critical given siblings like generate_password and nanoid) and whether bounds are inclusive, which are the behavioral facts an agent most needs.

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?

Two short sentences, front-loaded with the core action and followed by the performance characteristic. No filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a three-parameter tool with no annotations and no output schema, the description should state the return shape (single integer vs array when count > 1), bound inclusivity, and defaults for the optional max and count. None of these are covered, leaving meaningful gaps for correct 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 baseline is 3, and the schema descriptions are terse ('Minimum', 'Maximum', 'How many'). The description adds only the mapping of 'one or many' to the count parameter; it does not clarify whether max is inclusive, what happens if max is omitted, or what count defaults to.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Generate random integers in a range') plus the cardinality option ('one or many'), so the agent knows exactly what it produces. It does not distinguish itself from nearby siblings like random_data, dice, or coinflip, which is the only thing keeping it from a 5.

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?

There is no guidance on when to pick this over random_data, dice, coinflip, or generate_uuid, and no stated preconditions or exclusions. The agent must infer usage purely from the name and the phrase 'one or many'.

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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