generate_data_narrative

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

With no annotations, the description carries full burden for behavioral disclosure. It does not mention whether the tool is read-only, requires authentication, or has any side effects. The return structure is shown, but the underlying process (e.g., AI generation, data size limits) is not disclosed.

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 extremely concise: one sentence plus a return type annotation. It front-loads the purpose effectively. However, it could be slightly more informative without becoming verbose, e.g., noting that input must be a list of dicts from 'get_resource_data'.

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 and a defined output, the description is minimally adequate. It explains the return structure (which acts as an output schema), but it does not clarify the role of optional parameters like 'time_column' or 'entity_column' in generating the narrative. The schema descriptions help, but the tool could benefit from a brief usage hint.

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 coverage is 100%, so all parameters have descriptions. The description adds no extra meaning beyond the schema, such as explaining how 'time_column' influences the narrative or formatting expectations. Baseline 3 is appropriate since the schema already documents the parameters.

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 clearly states the tool generates a 'data story' with headline, big number, and narrative text. This distinguishes it from sibling tools like 'create_chart' for visualizations, though it could more explicitly differentiate from 'extract_data_insights' or 'data_profile' which also handle data summaries.

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?

No guidance is provided on when to use this tool over alternatives like 'extract_data_insights' or 'get_data_summary'. There are no prerequisites, exclusions, or context about appropriate use cases, leaving the agent to infer from the name alone.

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