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Duplicate calculated metric

duplicate_calculated_metric

Duplicate a calculated metric, optionally with a new name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesSource calculated metric ID (from list_calculated_metrics)
new_nameNoName for the copy

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoThe copy — its own new id, plus the name, formula and symbol.
successYesTrue when the call succeeded. A failure comes back as an error result instead.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput 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"
+}
  2. First observed

TDQS

B3.4/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations provide readOnlyHint=false and destructiveHint=false, so the agent knows this is a non-read, non-destructive operation, but the description adds no further behavioral context. It does not state that the original remains unchanged, whether the copy is independent, or if there are any side effects on related resources.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no filler. It states the action and the one optional modifier, making it appropriately concise for a simple two-parameter tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity, complete schema parameter coverage, and presence of an output schema plus annotations, the description is sufficient for correct invocation. It could mention the intended distinction from create/update, but the description is otherwise adequate for this simple tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters. The phrase 'optionally with a new name' adds mild clarity about new_name, but the description does not add significant meaning beyond what the schema already provides, warranting the baseline score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Duplicate a calculated metric' with the optional rename behavior. It clearly distinguishes this from siblings like create_calculated_metric, update_calculated_metric, and archive_calculated_metric.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explain when to choose duplicate over create or update, nor does it mention prerequisites such as obtaining the ID from list_calculated_metrics. The only hint about usage comes from the schema's parameter description, not the tool description itself.

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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