create_configuration

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

Annotations already declare readOnlyHint=false, destructiveHint=false, and idempotentHint=false. The description adds meaningful behavioral context beyond annotations: omitted fields inherit backend defaults, both dataset IDs are required for a runnable configuration, missing clean_dataset_id raises FileNotFoundError, ownership restrictions apply, and rejected datasets cannot be used.

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

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

The description is front-loaded with the core action and then covers the non-obvious constraints efficiently. Every sentence adds operational value: default inheritance, required dataset pairing, ownership checks, and rejected dataset exclusion.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 31-parameter mutation tool with no output schema, the description covers the most important non-obvious requirements: defaults, required dataset pairing, ownership validation, and rejected dataset restrictions. The schema supplies enums and numeric bounds for individual parameters, so the remaining omission of return behavior is minor.

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

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

Schema description coverage is only 16% across 31 parameters, so the description must carry significant semantic weight. It does explain the critical dataset_id/clean_dataset_id pairing, model_id ownership, default behavior for omitted fields, and rejected dataset restrictions, but it leaves most hyperparameters and configuration fields unexplained beyond their schema constraints.

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

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

The description states a specific verb and resource: 'Create a new pipeline configuration.' It clearly distinguishes creation from sibling configuration tools such as get_configuration, list_configurations, update_configuration, and get_default_configuration.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explains when to use this tool for creating a new configuration and explicitly points to get_default_configuration for omitted field defaults. It does not explicitly name update_configuration as the alternative for modifying existing configurations, so it falls short of full when/when-not guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.