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

With no annotations, the description carries the full burden of behavioral disclosure, but it only restates what the tool does and lists arguments. It does not describe rate limits, ordering, freshness, language of results, or what happens when no articles match the topic. The presence of an output schema helps, but the description itself adds little beyond the schema.

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?

The description is compact and front-loads the core purpose, followed by a clearly formatted Args block. Every sentence earns its place, and there is no filler or repetition.

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 simple two-parameter tool with an output schema, the description is largely complete: it defines the topic vocabulary, the count default/maximum, and the global scope. It only lacks explicit routing guidance among siblings and any caveats about result format, which are partially covered by the output schema.

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%, but the description compensates well by enumerating valid topic values (AI, Claude, OpenAI, MCP, OpenClaw, 스타트업, 개발, 클라우드) and stating count constraints (default 10, max 20). This adds meaning beyond the bare schema, though it does not explain subtle differences between overlapping topics.

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 uses a clear verb and resource: 'Get global AI/tech news by topic.' It indicates the tool fetches news and supports topic-based filtering, which distinguishes it from more generic siblings like news_search or read_article, though it never explicitly names those alternatives.

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 gives no explicit guidance on when to use this tool versus its siblings. It does not mention korean_news for Korean-only news, news_search for search queries, or trending for popularity, so an agent must infer usage solely from the tool name and the word 'global.'

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