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

With no annotations, the description carries the behavioral disclosure burden. It communicates the search scope and full-text nature, but does not mention result ordering, ranking, pagination, or whether results include excerpts, which would help an agent set expectations.

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 two sentences with no filler. The key action and scope are front-loaded, and every sentence earns its place.

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 search tool with only two fully documented parameters and no output schema, the description is nearly complete. It could mention what the response contains or how results are ordered, but this is a minor gap given the low complexity and strong schema coverage.

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 input schema already documents both parameters with 100% coverage, including an example for 'query' and a default/max for 'limit'. The description adds the 'full-text' context but does not add meaning beyond what the schema provides, so the baseline 3 applies.

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 specific verb ('search'), names the resource ('Finally Offline articles'), and clarifies the mechanism ('Full-text search') and scope ('across all'). It clearly distinguishes itself from list-based siblings like get_culture_news or get_trending_topics.

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 implies usage for finding specific topics, people, events, or trends, which gives the agent a sense of when to invoke it. However, it does not explicitly contrast with sibling tools or state when not to use it, leaving some routing decisions to inference.

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