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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds useful output artifacts (hooks, winners, fatigue, briefs) that the agent cannot infer elsewhere, but says nothing about processing cost, dataset size limits, or what happens if the dataset ID is invalid.

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 main sentence is literally repeated with an ellipsis truncation, which wastes the most prominent space and signals low editorial quality. Structure is otherwise short but broken rather than front-loaded.

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?

With no output schema, listing the derived artifacts partially compensates, but for a nested-object input tool the description omits input format expectations, failure behavior, and any differentiation from the sibling creative-intel tool.

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 nominally 100%, but the only nested 'input' object just links to an Apify URL, so the description's 'paste a dataset ID' is the only real signal about what to supply. That is a genuine addition, though it doesn't specify the expected ID format or source scraper conventions.

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?

States a transformation: Facebook Ad Library scraper results into 'AI creative intel' with named artifacts (hooks, winners, fatigue, briefs). However the lead sentence is duplicated and truncated ('hooks…'), and the description never distinguishes this tool from the near-identical sibling 'fb_ads_creative_intelligence', leaving the agent unsure which one to pick.

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?

'Paste a dataset ID. Works with any Meta ads scraper' hints at the prerequisite (an existing scraped dataset), but there is no explicit when-to-use, when-not-to-use, or alternative routing despite a confusingly similar sibling tool.

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