visualize_data

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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals that the 'data' key is injected automatically, requires a valid Vega-Lite spec, and mandates a prior upload step. However, it does not explicitly state that the tool is non-destructive or what happens with invalid specs, but the provided details are sufficient for safe use.

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 well-structured with clear 'when to use' and numbered steps. It is longer than a typical one-liner, but every sentence provides necessary guidance for constructing valid Vega-Lite specs, and the structure aids comprehension.

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's complexity and the presence of an output schema, the description covers prerequisites, usage steps, and critical constraints (e.g., doc link, schema validation, data injection). It gives an agent enough context to invoke the tool correctly, though it could mention error handling or result format.

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?

The schema has no descriptions for the parameters (0% coverage), but the description thoroughly explains both: 'name' refers to a registered dataset, and 'spec' is a Vega-Lite schema instance with specific constraints (e.g., no 'data' key). This fully compensates for the missing schema info.

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's purpose: 'render a Vega-Lite visualization of a registered dataset directly in the chat.' It uses a specific verb ('render') and resource ('Vega-Lite visualization'), and distinguishes it from the sibling tool 'upload_data' by focusing on visualization rather than data upload.

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 explicitly provides when-to-use guidance ('When the dataset is complex or multi-dimensional...') and when-not-to-use ('Not useful for single data points.'). It also gives a clear prerequisite workflow: upload the dataset first using 'upload_data' and then reference it by name.

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