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

The description presents a pure query/read operation (查询), while annotations declare readOnlyHint=false and destructiveHint=true. That is a direct contradiction, so the description actively misleads about the tool's behavioral profile. It also provides no compensating detail about permissions, side effects, or safety.

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 a single, front-loaded sentence with no filler. It states the resource and scope immediately and does not waste words.

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 with six optional parameters, no output schema, and annotations that conflict with the described read-only behavior, the description is too thin. It does not resolve the destructive/read-only ambiguity, does not explain what the returned status, consumption, or statistics contain, and gives no operational context.

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%, and all six parameters are documented in the schema with defaults, ranges, and meanings. The description adds no parameter-level meaning beyond what the schema already provides, so the baseline of 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 gives a specific verb (查询/query) and concrete resources (task status, consumption details, and user cumulative statistics) for the Dataify general collection API. It is clear what the tool does, but it does not differentiate itself from siblings such as web_unlock_statistics, scraper_task_status, or query_user_usage.

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 states what can be queried but gives no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. Any usage context must be inferred from the resource names alone.

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