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

Annotations already provide readOnlyHint, idempotentHint, openWorldHint. The description adds specifics: matches on name/tagline/category, case-insensitive substring, returns up to 20 results, and only searches live, published tools. This goes beyond annotations and clarifies behavior.

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?

Four concise sentences, front-loaded with purpose, then specificsahan. No fluff, every sentence adds value.

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 rich annotations (readOnlyHint, idempotentHint) and complete schema, the description covers scope, matching behavior, and result limit. Sufficient for an agent to invoke 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 already documents the query parameter well (100% coverage). The description adds matching details (fields searched, case-insensitivity) that clarify what the query is used for, enhancing beyond the schema's 'tool name, use-case, or category.'

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 tool searches a catalog of live, published AI tools, matching on name, tagline, or category. It explicitly says to use this for keyword-based discovery, distinguishing it from siblings like get_tool which likely fetches a specific tool. The 'Call this first' instruction further clarifies its role.

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 explicitly says to use this when users want to find, discover, or compare AI tools by keyword, which provides clear usage context. It doesn't explicitly exclude other tools (e.g., get_tool for known IDs), but the 'call this first' phrasing implies it's the entry point.

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