add_list

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

With no annotations, the description discloses key behaviors: the List is implemented as a Tablix with specific structure, the inner rectangle is named, and returns relevant fields. It does not cover side effects or permissions but provides substantial transparency.

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 concise, with every sentence adding value. It explains the RDL concept, the tool's behavior, and return value in a compact paragraph.

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 complexity (7 required params, no output schema, many siblings), the description provides essential information but lacks parameter details. It is adequate but has clear gaps.

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 input schema has 7 required parameters with 0% description coverage. The description does not explain any parameter details (e.g., format of top/left). Only dataset_name is implied by context. This leaves the agent with limited guidance.

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 adds a List (single-cell repeating Tablix) bound to a dataset. It explains the RDL representation and distinguishes from sibling tools like add_tablix_column.

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 context on when to use this tool (to create a repeating item per dataset row). It does not explicitly exclude alternatives but explains the List's nature, giving the agent enough information to choose appropriately.

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