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@arizeai/phoenix-mcp

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by Arize-ai

upsert-prompt

Create or update a prompt with a template and model configuration. Specify model provider, name, and temperature settings.

Instructions

Create or update a prompt with its template and configuration. Creates a new prompt and its initial version with specified model settings.

Example usage: Create a new prompt named 'email_generator' with a template for generating emails

Expected return: A confirmation message of successful prompt creation

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
descriptionNo
templateYes
model_providerNoOPENAI
model_nameNogpt-4
temperatureNo
Behavior2/5

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

The description claims 'Create or update' but only describes creation, creating ambiguity about the update case. No side effects, idempotency, or permission requirements are disclosed. With no annotations, the agent lacks critical behavioral context for a mutation tool.

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

Conciseness3/5

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

The description is relatively short but includes a redundant statement ('Create or update' vs 'Creates a new prompt') and an example that doesn't illustrate optional parameters. It could be more streamlined and informative.

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?

With 6 parameters, no output schema, and no annotations, the description fails to provide enough context for an agent to invoke correctly. Missing details include update semantics, parameter constraints, and return type beyond a vague 'confirmation message'.

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 only mentions 'template and configuration' and 'model settings' without detailing individual parameters. The example omits optional fields like model_provider, model_name, and temperature, so the agent gains little insight beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Create or update a prompt with its template and configuration', clearly indicating the action and resource. It distinguishes from sibling tools like get-prompt and list-prompts which are read-only. However, it does not clarify the update behavior, focusing only on creation.

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 or add-prompt-version-tag. The description does not mention prerequisites or when an update is appropriate, leaving the agent to infer context.

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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