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create-prompt-optimization-job

Create a prompt optimization job to automatically improve a registered prompt by tuning its configuration with algorithms, datasets, and scorers.

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
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It does not disclose whether the job runs asynchronously, what authentication is required, or any side effects. For a creation tool, behavioral details like return value and execution model are missing.

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

Conciseness5/5

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

The description is extremely concise: one sentence with no unnecessary words. It front-loads the core action and purpose.

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, the description should explain what the tool returns (e.g., job ID). It also lacks prerequisites (e.g., prompt must be registered) and execution behavior. The description is incomplete for a creation tool.

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 baseline is 3. The description adds no additional meaning beyond the schema; it does not explain parameter usage or semantics.

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 the verb 'create', the resource 'prompt optimization job', and the purpose 'automatically improve a registered prompt'. It distinguishes the tool from siblings like cancel or delete.

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?

The description implies usage when wanting to automatically improve a prompt, but it does not provide explicit guidance on when to use this tool versus alternatives (e.g., other optimization methods). No when-not or exclusions are 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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