Random-Generator
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| XBY_APIKEY | Yes | 你的实际apikey (Your actual API key) |
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_integerC | 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_uuidC | Generate a cryptographically secure UUID (v4) |
| generate_random_stringC | Generate a cryptographically secure random string |
| generate_random_choiceA | Randomly select items from a given list using cryptographically secure randomness |
| generate_random_booleanC | Generate cryptographically secure random boolean values |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
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 specific random generation tasks (boolean, bytes, choice, float, integer, string, UUID). There is no overlap or ambiguity between tools, as each handles a different data type or selection method with cryptographically secure randomness.
All tools follow a consistent verb_noun pattern with 'generate_random_' prefix (or 'generate_uuid'), using snake_case throughout. The naming is highly predictable and readable, making it easy to understand each tool's function at a glance.
With 7 tools, this is well-scoped for a random generation server, covering common use cases without bloat. Each tool earns its place by addressing a specific random generation need, making the set comprehensive yet manageable.
The tool surface provides complete coverage for random generation in a typical programming context, including booleans, bytes, choices, floats, integers, strings, and UUIDs. There are no obvious gaps, and agents can handle most random generation tasks without dead ends.