Generate one or more cryptographically random UUID v4 identifiers. Use this when you need unique IDs for test fixtures, database records, session tokens, or any scenario requiring a guaranteed-unique string. Returns up to 100 UUIDs in one call.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of UUIDs to generate (1–100, default: 1) |
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | ||
| uuids | No |
Changes observed during successful MCP inspections.
Input schema / examplesAdded value: +[
+ {
+ "count": 5
+ }
+]Input schema / properties / count / descriptionPrevious value: -"Number of UUIDs to generate (1–100, default: 1)"New value: +"Number of UUIDs to generate (1–100, default: 1)"Output schema / propertiesAdded value: +{
+ "count": {
+ "type": "number"
+ },
+ "uuids": {}
+}Output schema / (root)Previous value: -nullNew value: +{
+ "additionalProperties": true,
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the safety hints in the annotations, the description provides two critical behavioral facts: that the identifiers are 'cryptographically random' and that it 'Returns up to 100 UUIDS in one call.' This maximum limit is vital operational context.
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 impeccably structured, moving logically from definition to use cases, and ending with a key performance constraint (the 100-limit) without unnecessary filler.
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?
Given the strong input schema and comprehensive annotations, the description fills all remaining gaps by clarifying operational boundaries (UUID v4) and practical limits (100 maximum), making it complete for task execution.
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?
With 100% schema coverage, the baseline is 3. The description adds value by explicitly framing the parameter `count` as the mechanism for requesting multiple UUID strings and reiterating the functional purpose (guaranteed-unique string).
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 is highly specific, stating it generates 'cryptographically random UUID v4 identifiers.' It immediately distinguishes itself from generic string utilities (like hashing or encoding tools among the siblings) by defining its exact function and use cases.
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?
It provides excellent usage context by listing specific scenarios where the tool should be invoked ('test fixtures, database records, session tokens'). While it does not explicitly list alternatives not to use, its specialization makes the usage guidelines very clear.
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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