Pick a random whole number in an inclusive range, like spinning a "pick a number" wheel. Defaults to 1-100.
| Name | Required | Description | Default |
|---|---|---|---|
| max | No | Maximum value, inclusive. Defaults to 100. | |
| min | No | Minimum value, inclusive. Defaults to 1. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, and it does disclose the core behavior: a random whole number with inclusive bounds and default values. It does not mention side effects, error handling, or randomness guarantees, but for a simple stateless number picker this is adequate though not rich.
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 two concise sentences with the core operation front-loaded and no filler. The wheel metaphor and default summary both earn their place without bloating the text.
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?
For a low-complexity tool with two optional parameters fully documented by the schema, the description provides enough context: what the tool returns, the inclusive range behavior, and defaults. It could mention edge cases like min > max, but nothing essential is missing for normal invocation.
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 coverage is 100%, so the schema already documents min and max with defaults and inclusivity. The description adds only a summarized 'Defaults to 1-100' and the inclusive-range concept, which is already present in the schema, so no significant extra semantic value is added.
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 action ('pick'), the resource (a random whole number), and the key constraints (inclusive range, default 1-100). It is easily distinguished from the sibling wheel tools because it returns a number rather than operating on a wheel.
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 wheel analogy implies when a user would want this kind of random pick, and the defaults give immediate invocation context. However, it does not explicitly say when to use this tool over get_wheel/search_wheels/spin_wheel or provide exclusion criteria, so routing guidance is only implied.
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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Each tool has a clearly distinct purpose: fetching a saved wheel, searching wheels, spinning a list, and picking a random number. The descriptions make any potential overlap between random selection tools easy to resolve.
All tool names follow a consistent lowercase snake_case verb_noun pattern: get_wheel, pick_random_number, search_wheels, spin_wheel. The one pluralization difference is natural and does not hurt predictability.
Four tools is a well-scoped set for this domain. Each tool serves a distinct user need without unnecessary duplication or bloat.
Core use cases are covered: finding, retrieving, and spinning wheels, plus numeric random picks. Missing create/update/delete operations for saved wheels is a minor gap, but users can still accomplish random selection tasks without persistence.