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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive, so the safety profile is covered. The description adds genuinely non-derivable context: pricing at ¥0.2 per call, billing only on success, and automatic refund on failure or empty results — which tells the agent an empty return is a normal outcome rather than an error. It does not discuss rate limits or throttling.

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?

Four short sentences, ordered from purpose to return fields to use case to billing, with the core identity of the tool front-loaded. No filler, no restatement of the title, and the billing caveat — the one thing an agent could act on wrongly — is included compactly.

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 sentence enumerating returned fields does the job of describing the response shape, and the billing note clarifies the failure/empty-result semantics. What remains missing is the identifier format for user_id and any note on how stale or cached the profile data may be.

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%, so the baseline is 3. The description adds no meaning beyond the schema for either parameter; notably it never clarifies what form user_id takes (numeric UID versus a sec_uid style identifier), which is the most likely source of a bad call.

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 verb and resource (获取快手用户信息) and enumerates exactly what comes back: nickname, follower count, like count, bio, and verification status. The 'ks_' prefix and explicit platform naming make it distinguishable from bili_user_info, douyin_author_info, and the sibling ks_post_detail / ks_user_posts without opening the schema, though no sibling is named explicitly.

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?

It gives concrete usage contexts — 达人筛选 (influencer screening), 账号画像 (account profiling), and 粉丝量级分组 (follower-tier grouping). That is clear when-to-use guidance. It stops short of exclusions or pointing to alternatives such as ks_user_posts when post-level data is actually wanted, so it does not reach a 5.

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