Pluggedin Random Number Generator
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| generate_random_integerA | Generate cryptographically secure random integers within a specified range |
| generate_random_floatB | Generate cryptographically secure random floating-point numbers |
| generate_random_bytesC | Generate cryptographically secure random bytes |
| generate_uuidA | Generate a cryptographically secure UUID (v4) |
| generate_random_stringB | Generate a cryptographically secure random string |
| generate_random_choiceA | Randomly select items from a given list using cryptographically secure randomness |
| generate_random_booleanB | Generate cryptographically secure random boolean values |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| generate_random | Help me generate random values using cryptographically secure methods |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 7 tools
Every tool has a clearly distinct purpose targeting different types of random data generation: boolean, bytes, choice selection, float, integer, string, and UUID. There is no overlap in functionality, making tool selection straightforward for an agent.
All tools follow a consistent 'generate_random_' prefix pattern (except 'generate_uuid' which logically fits as a special case), with snake_case used uniformly. This predictable naming scheme makes the tool set easy to navigate and understand.
With 7 tools, the server is well-scoped for random data generation, covering common use cases without being overwhelming. Each tool earns its place by addressing a specific type of random output, making the count appropriate for the domain.
The tool set provides complete coverage for random data generation, including boolean, numeric (integer and float), string, bytes, selection from lists, and UUIDs. There are no obvious gaps; agents can handle a wide range of randomization tasks without dead ends.