get_dataset_items

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Get items' implies a read operation, but it doesn't specify whether this is paginated (hinted by offset/limit in schema but not described), what the response format is (no output schema), or any constraints like rate limits or authentication needs. The description adds minimal context beyond the basic action.

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 a single, efficient sentence ('Get items from a dataset.') with zero wasted words. It's front-loaded and appropriately sized for a simple tool, making it easy to parse quickly without unnecessary elaboration.

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?

Given the tool has 5 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain the return values (e.g., structure of items), behavioral aspects like pagination or error handling, or how it differs from siblings. For a data retrieval tool with multiple parameters, more context is needed to guide effective use.

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 100%, meaning all parameters (dataset_id, offset, limit, clean, fields) are documented in the schema with descriptions. The description adds no additional meaning about parameters, such as explaining what 'clean' entails beyond the schema's 'Remove empty items and hidden fields'. Baseline score of 3 is appropriate since the schema does the heavy lifting.

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 'Get items from a dataset' clearly states the verb ('Get') and resource ('items from a dataset'), making the purpose understandable. However, it doesn't differentiate this tool from similar siblings like 'get_dataset' (which might retrieve metadata) or 'get_run_dataset_items' (which might retrieve items from a run-specific dataset), leaving the scope vague regarding what distinguishes it.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid dataset_id), exclusions, or comparisons to siblings like 'list_datasets' (for listing datasets) or 'get_run_dataset_items' (for run-specific items), leaving the agent to infer usage from context alone.

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