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

Annotations already mark this as readOnly and non-destructive. The description adds useful behavioral context: it is a capability catalog containing required/optional parameters, per-request limits, and unit price, and it does not execute scraping. It does not mention pagination or output structure, but that is a minor gap for a simple discovery tool.

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?

Two sentences deliver dense, relevant information: the first states the resource and its contents; the second states when to use it, what it reveals, and which sibling to use for chat. No filler or redundancy.

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 no required parameters, no output schema, and simple read-only annotations, the description supplies enough context for an agent to call it correctly: the purpose, the optional filter, the data it exposes, and the intended sequencing before everyinfra_call_api.

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 the single optional platform parameter is already documented with examples. The description relates platform to the broader workflow (check platform/action before calling the API) but does not add extra meaning about the parameter itself, such as what happens when it is omitted.

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 action ('列出...平台与数据抓取能力') and resource, with concrete scope (87 平台 / 387 项) and categories (搜索/详情/评论/主页等). It also clearly separates this tool from everyinfra_call_api and everyinfra_chat.

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 explicitly says to use this before calling everyinfra_call_api to inspect platform/action, parameters, max_limit, and pricing. It also provides an exclusion: AI conversations should use everyinfra_chat instead, and it notes this only covers data scraping.

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