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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description doesn't need to restate that. It adds valuable behavioral details: case-insensitive substring matching on three fields, and a result cap of 20. This goes beyond annotations but doesn't cover pagination or sorting, which is minor given the output schema and simplicity.

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?

Two concise sentences: the first covers purpose and matching scope, the second provides usage guidance and examples. No filler, front-loaded with the core purpose, and 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 the simple tool (1 parameter, no nested objects) and presence of an output schema, the description fully covers what the agent needs: what it searches, how it matches, the usage context, and result limit. It is complete for its complexity level.

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 schema already describes query as 'Free-text search term', but the description enriches it with what it matches against (name, tagline, category) and the case-insensitive nature. With 100% schema coverage, baseline is 3, but the added semantics about matching logic earns a 4.

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 the 'Beste KI Tools catalog' of live, published AI tools by free-text query, matching on name, tagline, or category. This specific verb+resource+scope distinguishes it from siblings like get_tool (exact retrieval) and list_alternatives (alternative discovery), and includes concrete examples.

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?

It explicitly instructs to 'Call this first when a user asks to find, discover, or compare AI tools by keyword, use-case, or category', providing clear guidance on when to use. It also gives example queries ('agents', 'writing assistants'). The mention of 'first' implies it's the entry point, aligning with sibling tools for follow-ups, though it doesn't enumerate exclusions. Still, the explicit directive is strong.

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