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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds only the return shape ('the LIST of items') and says nothing about pagination ceilings, default limit behavior, ordering, or what happens when the dataset is empty or the run is still in progress — meaningful gaps with no output schema to fall back on.

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 short, front-loaded sentences with no filler; the return shape is stated immediately. It is efficient, though nearly too terse given the tool's parameter surface.

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 an 11-parameter read tool with no output schema, the description confirms only what comes back at the coarsest level. Given that annotations already handle safety, the remaining need is pagination and projection semantics, which are absent.

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 64%, and the description adds no parameter meaning at all. Undocumented params such as `omit`, `fields`, `limit`, and `offset` carry real behavioral weight (projection, pagination) but are explained in neither schema nor description, so an agent cannot use them confidently.

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 and resource: read the results/items a run produced, tied to the schema's `dataset_id` which is defined as the run's `defaultDatasetId`. This is enough to separate it from run-lifecycle siblings like apify_run_status or apify_abort_run, though no sibling is named explicitly.

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 this versus apify_run_status, apify_run_sync, or apify_run. Nothing says whether the run must be finished first, or how to page through large result sets, so the agent must infer sequencing from the surrounding tool family.

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