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mlflow-mcp-server

create-prompt-optimization-job

Automatically improve a registered prompt by creating an optimization job. Configures algorithm, dataset, and scorers to refine prompt performance.

Instructions

Create a prompt optimization job to automatically improve a registered prompt

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
experimentIdNoExperiment ID (defaults to MLFLOW_EXPERIMENT_ID if unset)
sourcePromptUriYesURI of the source prompt to optimize (e.g. 'prompts:/my_prompt/1')
configNoOptimizer configuration object (algorithm, dataset, scorers, etc.)
tagsNoTags to attach to the job
Behavior3/5

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

Annotations indicate readOnlyHint=false and openWorldHint=true, so description doesn't need to repeat that. However, the description does not disclose any additional behavioral traits such as job duration, asynchronicity, or required permissions beyond the annotation implications.

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 a single concise sentence with no wasted words. However, it could be slightly more structured (e.g., bullet points for clarity) but it is efficient.

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?

No output schema exists, and the description does not mention return values (e.g., job ID). The 'config' parameter with nested objects is not elaborated on, leaving the agent without important usage details.

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?

Schema coverage is 100%, so parameter descriptions in the schema are complete. The tool description does not add new meaning beyond the schema; it just restates the overall purpose.

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 clearly states the verb 'Create' and the resource 'prompt optimization job', and explains the purpose 'automatically improve a registered prompt'. It is specific enough to distinguish from sibling tools like delete or get jobs, but could be more specific about what 'improve' entails.

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 vs alternatives (e.g., manual prompt editing) or prerequisites (e.g., the prompt must already be registered). The description lacks context for usage decisions.

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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