duplicate_calculated_metricDuplicate a calculated metric, optionally with a new name.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Source calculated metric ID (from list_calculated_metrics) | |
| new_name | No | Name for the copy |
| Name | Required | Description | Default |
|---|---|---|---|
| data | No | The copy — its own new id, plus the name, formula and symbol. | |
| success | Yes | True when the call succeeded. |
Changes observed during successful MCP inspections.
Input schema / $schemaRemoved value: -"http://json-schema.org/draft-07/schema#"Output schema / $schemaRemoved value: -"http://json-schema.org/draft-07/schema#"Output schema / properties / success / descriptionPrevious value: -"True when the call succeeded. A failure comes back as an error result instead."New value: +"True when the call succeeded."Output schema / (root)Previous value: -nullNew value: +{
+ "$schema": "http://json-schema.org/draft-07/schema#",
+ "additionalProperties": false,
+ "properties": {
+ "data": {
+ "additionalProperties": {},
+ "description": "The copy — its own new id, plus the name, formula and symbol.",
+ "type": "object"
+ },
+ "success": {
+ "description": "True when the call succeeded. A failure comes back as an error result instead.",
+ "type": "boolean"
+ }
+ },
+ "required": [
+ "success"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate non-read-only and non-destructive, but the description adds no further behavioral context. It does not state that the original metric remains unchanged, whether the copy is deep or shallow, or if permissions and dependent widgets are duplicated. For a mutation-like operation, this is a notable gap.
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 a single, front-loaded sentence with no fluff. It efficiently conveys the action and the optional naming capability.
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 tool with only two parameters and an output schema, the description is largely sufficient for correct invocation. Its main gap is missing behavioral details like side effects, but the schema covers the required inputs and the output schema handles return values.
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?
The input schema provides complete descriptions for both parameters (id and new_name), so the description adds little beyond restating that new_name is optional. A baseline of 3 is appropriate given 100% schema description coverage.
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 uses the specific verb 'Duplicate' with the resource 'calculated metric', making the operation unambiguous. This clearly distinguishes it from siblings like create_calculated_metric and update_calculated_metric, despite not naming them.
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?
There is no guidance on when to use this tool versus alternatives such as create_calculated_metric (for new metrics) or archive_calculated_metric (for removing metrics). The agent must infer usage solely from the tool name and generic action word.
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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