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ncloud_create_custom_schema

Create a custom schema in Cloud Insight to define fields and dimensions for custom metrics.

Instructions

Create a user-defined custom schema in Cloud Insight for custom metrics.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsYesSchema field definitions
prodNameYesProduct name(s) for the custom schema
useCustomResourceNoWhether to use custom resource (default false)
Behavior2/5

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

Annotations only include destructiveHint: false, so the description carries the burden of behavioral disclosure. It adds no information about idempotency, validation rules, failure modes, or any side effects beyond the generic 'create'. The description essentially restates the operation without enriching the agent's understanding.

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?

A single sentence with no filler or redundancy. It front-loads the action and resource, and every word contributes to the intended meaning.

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

Completeness2/5

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

The tool has no output schema and a non-trivial nested fields parameter, yet the description provides no workflow context, return value expectations, or usage notes. It does not explain what a custom schema is for beyond 'custom metrics', why prodName is an array, or how field types map to metrics. The agent would need to rely heavily on the schema and external knowledge.

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%, with each parameter having a basic description (e.g., fieldType enum, prodName as product names). The description text adds no extra parameter semantics, but the schema already provides adequate names and types, meeting the baseline for adequate coverage.

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 clearly states the action ('Create'), the resource ('a user-defined custom schema'), and the context ('in Cloud Insight for custom metrics'). This verb+resource+context pattern makes the tool's purpose specific and distinguishable from siblings like ncloud_update_product_schema or ncloud_create_custom_resource.

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

Usage Guidelines3/5

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

The description implies the use case via 'for custom metrics' but does not explicitly state when to use this tool versus alternatives or mention any exclusions or prerequisites. It provides enough context to infer purpose but stops short of clear guidance relative to the large sibling set.

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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