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Arize-ai

@arizeai/phoenix-mcp

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by Arize-ai

get-prompt-version-by-tag

Retrieve a prompt version by its tag name. Get the template, model configuration, and invocation parameters for a tagged version.

Instructions

Get a prompt version by its tag name. Returns the prompt version with its template, model configuration, and invocation parameters.

Example usage: Get the 'production' tagged version of prompt 'article-summarizer'

Expected return: Prompt version object with template and configuration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
prompt_identifierYes
tag_nameYes
Behavior3/5

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

With no annotations, description carries the burden. It states the function is a read operation and specifies the return shape. However, it does not disclose error behavior (e.g., missing tag), authorization needs, or rate limits. Adequate but not comprehensive.

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

Conciseness4/5

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

Description is brief (two sentences) plus example and expected return. No unnecessary words. Well-structured with clear sections. Could be slightly more concise by integrating example into description, but overall efficient.

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?

No output schema, but description outlines return structure. For a simple retrieval tool, it covers key aspects. However, lacks details on edge cases (tag not found, multiple tags) and how it fits with sibling tools like add-prompt-version-tag and list-prompt-version-tags. Partially complete.

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

Parameters2/5

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

Input schema has 0% description coverage. Description provides an example hinting that prompt_identifier can be a prompt name, and tag_name is a string, but does not define acceptable values, formats, or whether prompt_identifier is ID or name. The example partially compensates but leaves ambiguity.

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?

Clearly states action ('Get'), resource ('prompt version'), and retrieval method ('by its tag name'). Also specifies what is returned (template, model configuration, invocation parameters). Distinguishes from sibling tools like get-prompt-version (likely by version ID) and get-prompt.

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?

Provides an example use case ('Get the production tagged version...') which implies when to use, but lacks explicit guidance on when not to use or how it compares to alternatives like get-prompt-version. No exclusion criteria or prerequisites mentioned.

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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