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

The description frames this as a read (查询 account info, phone, registration), yet annotations declare readOnlyHint=false and destructiveHint=true. That is a direct conflict about whether the tool mutates state, which is exactly the signal an agent needs before invoking. The description also does not reconcile this or explain any write/verification side effect.

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?

A single front-loaded sentence that enumerates the returned fields with no filler. It is appropriately sized for the tool's simplicity. Slight deduction because it neither signals read-only intent nor resolves the destructive-hint mismatch, leaving the most important sentence unwritten.

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 0-param tool with no output schema, the description adequately conveys what data comes back (account, registration date, masked phone, real-name verification). However, it omits any statement about state mutation, which is critical given contradictory destructive annotations, and gives no guidance on the sibling user-query tools.

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 schema has zero parameters, so there is nothing for the description to document; baseline is 4. The description usefully clarifies that the lookup key is the request token (implicit auth context) rather than an input argument, which is the only semantic gap a 0-param schema could leave.

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 (查询) and a concrete resource set: Dataify user account info, registration date, masked phone number, and real-name verification. This clearly distinguishes it from siblings like query_user_balance, query_user_usage, and query_user_api_keys. It does not explicitly name those siblings, but the resource scope is unambiguous.

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?

No when-to-use guidance, no prerequisites, and no mention of the alternative user-query siblings that an agent must choose between (balance, usage, api_keys). The token-based context is stated but that is a precondition, not usage guidance. The agent must infer selection criteria from the name alone.

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