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Arize-ai

@arizeai/phoenix-mcp

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by Arize-ai

list-prompts

Retrieve a list of prompts with IDs, names, and descriptions to review and manage LLM prompt templates and their model parameters.

Instructions

Get a list of all the prompts.

Prompts (templates, prompt templates) are versioned templates for input messages to an LLM. Each prompt includes both the input messages, but also the model and invocation parameters to use when generating outputs.

Returns a list of prompt objects with their IDs, names, and descriptions.

Example usage: List all available prompts

Expected return: Array of prompt objects with metadata. Example: [{ "name": "article-summarizer", "description": "Summarizes an article into concise bullet points", "source_prompt_id": null, "id": "promptid1234" }]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
Behavior2/5

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

With no annotations, the description carries full burden to disclose behavior. It claims to return 'all' prompts but the limit parameter contradicts this. It does not state read-only nature, pagination, or auth requirements. The example output is helpful but insufficient for transparency.

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?

The description is concise at ~10 lines, front-loads the main purpose, and includes a helpful example. Minor redundancy ('Get a list' vs 'List all') but overall well-structured for quick comprehension.

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?

For a simple list tool with one optional parameter, the description provides context on what a prompt is and what the return looks like. However, it fails to explain the limit parameter behavior, and the output schema is absent. Adequate but incomplete.

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

Parameters1/5

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

Input schema has 0% description coverage, and the description does not mention the 'limit' parameter at all. Saying 'all the prompts' misleads agents about the effect of the limit. No parameter details are provided beyond what the schema offers.

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 opening line 'Get a list of all the prompts' clearly states the tool's action and resource. The description distinguishes it from sibling tools like get-prompt (single retrieval) by implying it returns multiple prompts. The purpose is unambiguous.

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?

No explicit guidance is given on when to use this tool versus alternatives like get-prompt, get-prompt-by-identifier, or list-prompt-versions. The description lacks 'when to use' and 'when not to use' statements, leaving inference to the agent.

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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