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@arizeai/phoenix-mcp

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by Arize-ai

add-prompt-version-tag

Tag a specific prompt version with a label such as 'production' to organize and identify it. Use this to manage prompt versions within Phoenix.

Instructions

Add a tag to a specific prompt version. The operation returns no content on success (204 status code).

Example usage: Tag prompt version 'promptversionid1234' with the name 'production'

Expected return: Confirmation message of successful tag addition

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
descriptionNo
prompt_version_idYes
Behavior3/5

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

Without annotations, the description discloses the 204 status code and expected confirmation message, but does not discuss error cases, idempotency, or effects of duplicate tags.

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 concise, well-structured with separate sections for example and expected return, and front-loads the purpose.

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

Completeness3/5

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

Given the tool's simplicity and lack of annotations/output schema, the description is moderately complete but missing details on error handling and tag constraints.

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?

With 0% schema coverage, the description partially compensates via an example showing `prompt_version_id` and `name`, but does not explain the `description` parameter or provide detailed parameter semantics.

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 tool adds a tag to a specific prompt version, includes an example, and distinguishes from siblings like list-prompt-version-tags.

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 provide guidance on when to use this tool versus alternatives (e.g., listing tags or other operations), nor does it mention prerequisites or restrictions.

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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