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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds meaningful context: it is a blocking call and capped at 300 seconds, which are important behavioral traits not covered by annotations. No contradiction.

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 and front-loaded with the core purpose. It includes a helpful example without excessive verbosity. Every sentence contributes, though the example could be seen as slightly long for a description.

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 tool that runs an external actor, the description explains the blocking nature, timeout, and that results are returned. It does not cover error handling or failure modes, but given the annotations and schema richness, it is sufficiently complete for an agent to call it correctly.

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 are already described in the schema. The description adds an example and clarifies that input shape is actor-specific, which is useful but does not go beyond the schema's descriptions. Baseline 3 is appropriate.

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 action (run an Apify Actor) and the resource, plus that it returns dataset results in a single blocking call. It does not explicitly distinguish from sibling tools like apify_dataset_items, but the purpose is unambiguous and specific.

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?

It mentions a single blocking call and a 300-second cap, which implies usage context, but it does not explicitly state when to prefer this over apify_dataset_items or other alternatives. There is no exclusion criteria, but the example gives practical guidance.

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