data_story

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

No annotations are provided, so the description must carry the full behavioral burden. It only hints at the output format (narrative with charts) and says nothing about side effects, dependencies, required permissions, how table_name and theme affect behavior, or any limitations. This is insufficient for a tool with no annotation context.

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 very short, but 'Data Story:' redundantly repeats the tool name. The remaining phrase is under-specified rather than economically complete, and there is no structure to help an agent extract key directives quickly.

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?

Even though an output schema exists and the tool has only two parameters, the description still misses crucial context: how this tool differs from visualize_data or smart_summary, what inputs mean, and what behavior to expect. The minimal description leaves significant gaps for safe invocation.

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 0%, and the description mentions neither table_name nor theme. It does not explain that table_name is the data source or what theme controls. Since the schema provides only names and types, the description adds no semantic value for 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 says the tool produces a 'narrative with charts' and a 'coherent story about data', which conveys an intent but no explicit verb like 'generate' or 'create'. It also does not distinguish this tool from siblings such as visualize_data, smart_summary, or auto_insights, leaving the precise purpose somewhat vague.

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?

There is no guidance on when to use data_story versus its many sibling tools. The description implies it is for creating narrative data reports, but it never states the conditions, exclusions, or alternatives, so an agent cannot make an informed choice.

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