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@arizeai/phoenix-mcp

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by Arize-ai

list-prompts

List all prompt templates with their metadata including IDs, names, and descriptions to manage LLM input configurations.

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?

No annotations are provided, so the description must disclose behavior. It states it returns a list of prompt objects but does not clarify read-only nature, authentication needs, or any side effects. The limit parameter's effect is not explained.

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 relatively concise with a clear structure: purpose, definition, expected return, and example. The definition of prompts may be slightly redundant but adds context without excessive length.

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?

Given no output schema and one optional parameter, the description fails to mention pagination or that the limit constrains results. The phrase 'list of all the prompts' is misleading when limit defaults to 100. No return type details beyond example.

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?

Schema description coverage is 0%, yet the description does not mention the 'limit' parameter. The agent must infer its meaning from the schema alone, which is insufficient for complete understanding.

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 'Get a list of all the prompts' and defines what a prompt is. It distinguishes the tool from others by specifying it returns a list of prompts, not versions or individual prompts.

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 guidance on when to use this tool versus siblings like get-prompt or list-prompt-versions. The description does not provide context for selecting this tool over alternatives.

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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