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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It transparently reveals the multi-source search behavior, fallback mechanism to AI, and that AI results are 'clearly-labeled' with a 'source' field. However, it doesn't mention rate limits, caching freshness, or whether this is a read-only operation. The AI fallback disclosure is valuable and goes beyond basic tool purpose.

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 three sentences long, front-loaded with the core purpose and then detailing the fallback mechanism. Every sentence adds value, but the structure could be slightly tighter: the last sentence about the 'source' field could be integrated into the second sentence. Still, it is efficient and clear.

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?

Given the tool's relative complexity (multi-source search with fallback) and no output schema, the description adequately explains data freshness, source labeling, and the content types. It lacks pagination or return format details, but the 'per_page' parameter and source field provide enough context for an agent to use it correctly.

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 67%: the 'type' and 'search' parameters have descriptions, while 'per_page' does not. The description adds no additional parameter details beyond the schema. With moderate coverage, the description does not compensate for the missing 'per_page' description, but the parameter is self-explanatory (a standard pagination parameter) and has clear defaults/min/max. The description adds context about the output 'source' field, which indirectly enhances understanding of 'type' results.

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 clearly states the verb 'Search' and the resource 'Iconic Expeditions content across itineraries, activities, destinations, and posts', distinguishing it from siblings like 'get_content' (specific item retrieval) and 'search_wp_content' (WordPress-only). The specific content types are listed, making the scope unambiguous.

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 explains the content chain flow (WordPress -> local cache -> AI fallback) and how gaps are filled, but it does not explicitly state when to use this tool over alternatives like 'search_wp_content' or 'get_content'. The context is clear for when this tool covers multiple sources, but no exclusions or when-not-to-use guidance are provided.

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