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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the agent knows this is a safe, non-destructive, closed-world read operation. The description adds value by revealing that the search is across every board, and that the output is ranked. However, it does not describe pagination behavior, ordering details, or what happens if the query matches many products. For a search tool, this is adequate but not highly transparent beyond annotations.

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 a single, dense sentence that conveys purpose, scope, return values, and tool chaining. No word is wasted. It is front-loaded and highly efficient.

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 low parameter count (2), high schema coverage for the required parameter, clear annotations (read-only, non-destructive, closed-world), and the existence of an output schema, the description is complete. It explains the search scope (all boards), the returned fields, and how the output connects to sibling tools. The agent has sufficient information to use and chain this tool 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 coverage is 50% (2/4 properties described—only 'query' has a schema description). The description adds value by explaining that 'name or brand' are the searchable fields, which is more specific than the schema's generic 'Product or brand name' and reinforces the query's scope. It does not add detail about the 'limit' parameter, but the schema already provides a default and bounds. The description compensates for the partial schema coverage by clarifying search semantics.

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 specifies a clear verb ('Find') and resource ('ranked products'), and distinguishes the tool by noting it searches by name or brand across every board. It explicitly states what it returns (slug, category, tier) and hints at its role as a prerequisite for 'get_product' and 'get_tier_list', differentiating it from siblings like 'get_product' or 'what_to_avoid'.

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 clearly explains when to use this tool: to find products by name or brand across all boards. It tells the agent that the returned values are what 'get_product' and 'get_tier_list' need next, effectively providing a chaining pattern and an implicit alternative (those tools are for after you have the identifiers). This is explicit usage guidance.

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