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

Annotations already cover the safety profile (readOnly, openWorld, non-destructive), and the description adds high-value behavior they cannot express: the $0.0155 USDC per-call cost, the x402 payment path across four chains, that compliant MCP clients pay automatically, and the per-item shape (rank, title, url, score). This is exactly the extra context the annotations leave out.

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?

It is front-loaded with the purpose, then parameters, then price/payment, so the important content comes first. The two-sentence pricing block and the trailing sample-input hint are slightly verbose, but each still carries actionable information.

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 still tells the agent what items look like (rank, title, url, score, with the score's meaning varying by source), documents all five parameters, and discloses cost and payment mechanics. Only obscure edge cases (per-source failures, pagination) are unaddressed.

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 0%, so the description must carry the full burden and it does: sources (default all), limit (1–50, default 10), language (Wikipedia/Google News, default en), country (Google News, default US) and since (GitHub daily/weekly/monthly) are all explained, including which sources each parameter actually affects.

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 names a specific deliverable (what is trending right now) and enumerates every source it draws from: Hacker News, GitHub, Wikipedia, Google News, Baidu and Bilibili. This instantly distinguishes it from siblings like news_search and discussion_search, so an agent can route without opening the schema.

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 enumerated source list gives clear context for when this tool applies (aggregated hot-list/trend data across tech, news and China platforms), and the free-sample call hint tells the agent how to probe it cheaply. It stops short of naming alternatives or stating when not to use it (e.g., vs news_search for a single story).

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