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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds the non-obvious behavioral detail that query settings are preserved across the expansion, which helps set expectations about how the continuation works. It does not contradict any annotation.

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?

Two sentences, with the action and object front-loaded and the input contract in the second sentence. There is no repetition of schema fields or annotation properties, and every clause adds new information.

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?

For a simple two-parameter tool with annotations and an output schema, the description covers the essential contract: what to pass, what operation occurs, and that query settings are retained. Minor omissions like continuation-token expiry or invalid-ID handling exist, but the low complexity and presence of an output schema keep this from being a significant gap.

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?

With 0% schema description coverage, the description carries the semantic burden. It defines result_id as identifying a prior Data Parrot result and continuation_id as one that was returned by that prior result, providing the key relational meaning missing from the schema. It does not detail ID formats or error behavior, but the core meaning of both parameters is conveyed.

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 states a specific verb ('load') and resource ('more data or supporting evidence from a prior Data Parrot result'), which clearly distinguishes this tool from the sibling data-getters and workspace-management tools. The reference to continuation_id makes the pagination/expansion purpose unmistakable.

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 gives clear invocation context: use it after you already have a result_id and a continuation_id returned from a prior result, and it explicitly preserves query settings. It does not contrast this with sibling tools, but the continuation_id prerequisite is an unambiguous trigger that makes the appropriate usage scenario evident.

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