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

Annotations already declare the safety profile (openWorldHint=true, destructiveHint=true, readOnlyHint=false), so the description need not repeat it. It adds useful behavioral context — posts are labeled sponsored/self-paid with evidence, plus sentiment and brand mentions, and no login is required — but says nothing about billing/credit consumption or long-run polling, which matter for a paid Apify Actor.

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, well-sized, with the core function front-loaded after a short meta clause. The opening 'calls the Actor ... and retrieves its output results' is boilerplate filler, but nothing else is wasted.

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 14-parameter tool with an output schema, return values need no explanation, and the description covers the scraping scope and what each result contains. The main omission is cost/credit behavior for the paid judgments, but annotations and schema carry most of the remaining burden.

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 description coverage is 100% across 14 parameters, so the schema already documents every field (queries, judge, brands, date range, proxy options). The description adds only indirect meaning ('posts by keyword' maps to queries, the labels map to the judge flags) and no syntax or defaults, making the baseline 3 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?

States a specific verb and resource: it queries Naver Blog posts by keyword and labels each one sponsored/self-paid with sentiment and brand mentions. The Naver Blog scope cleanly distinguishes it from siblings like naver-shopping-rank-tracker and korean-review-classifier. It stops short of naming a sibling alternative, so it does not fully earn a 5.

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 implies the use case (Korean social listening / brand monitoring on Naver Blog) and notes 'no login,' but never states when to pick this over siblings such as korean-review-classifier or kbeauty-ranking-review-monitor, nor any exclusions. Usage is inferable but not spelled out.

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