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

With no annotations provided, the description carries the full behavioral burden and does well by disclosing the saved-statistics source (latest.json), that counts are snapshot-based rather than live, the absence of a date field, and that summed users are not deduplicated. It does not explicitly state read-only behavior, but that is strongly implied by a listing operation.

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 front-loaded with the purpose and then adds only relevant caveats about data provenance and aggregation. Every sentence earns its place, and there is no redundant restatement of the tool name.

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?

Given a zero-parameter tool with an output schema and no annotations, the description provides enough context to call it correctly: what it returns, where the data comes from, and the key limitations of the returned counts. Nothing essential is missing.

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?

The tool has zero parameters, so there is no parameter syntax or meaning to explain. The baseline for zero-parameter tools is 4, and nothing in the description creates ambiguity about inputs.

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 resource (websites in the filtered scraper export) and exactly what metrics are returned (actor count and summed 30-day users per website). It is clear without opening the schema, though it does not explicitly differentiate itself from siblings such as find_scrapers or compare_scrapers.

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 it is for inspecting websites in a filtered scraper export, but it gives no explicit when-to-use guidance and names no alternatives or exclusions. It also does not clarify when to prefer this over sibling comparison or search tools.

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