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

Annotations already cover the safe-read profile (readOnlyHint, idempotentHint, destructiveHint=false). The description adds the auth requirement (【需要登录】) and explains what several returned keys actually mean (e.g. nudge reaching via email/SMS and where one-click unsubscribe lands), which goes beyond the annotations.

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?

Front-loads the login requirement and the core action, then enumerates the keys compactly with inline glosses. It is long, but the length is largely justified given there is no output schema; it stops short of 5 because the key list is dense and could be trimmed.

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, the description carries the full burden of explaining the return content and does so by naming all 12 keys with meanings, plus the disambiguation block. Nothing an agent needs to call and interpret this tool 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 takes zero parameters, so per the baseline rule a 4 applies. The schema is empty and there is nothing for the description to disambiguate; the enumeration of returned keys is return-value documentation rather than parameter guidance.

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 (返回) and resource (全部 12 个通知偏好) and even enumerates the exact keys returned. It clearly separates itself from siblings by naming set_notification_prefs as the mutation counterpart.

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?

Explicitly routes the user: '改用 set_notification_prefs' for changing values, and the 【别搞混】 block directs 'who to meet / don't recommend' to list_my_match_preferences and interest tags to get_my_preferences. When-to-use and when-not-to-use are both spelled out.

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