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

With no annotations provided, the description carries the full burden and delivers thoroughly. It reveals ranking internals (gte-small embeddings + cosine similarity), the meaning of ranking_mode, result fields including security_score and risk_level, and the critical interpretation of critical_findings > 0. This is rich, non-obvious behavioral context that goes far beyond a typical one-line summary.

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 compact: four sentences that progress logically from what the tool does, to how results are ranked, to what results contain, to the recommended follow-up with get_server. Every sentence adds necessary information with no fluff or repetition of schema details.

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?

Despite having 7 parameters and no output schema, the description supplies enough context for an agent to use the tool effectively: semantic search behavior, response field expectations, and safety-critical guidance around critical_findings. The only missing pieces (pagination defaults, error behavior) are adequately covered by the schema or are not essential for a search tool.

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 covers all 7 parameters with individual descriptions, so the baseline is 3. The description adds above-baseline value by explaining how query interacts with semantic ranking, how sort defaults change based on query presence, and why the transport filter excludes SSE (a known catalog limitation). These insights are not present in the schema alone.

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 opens with a specific verb and resource ('Search the MCP Marketplace catalog') and immediately clarifies the search mechanism (semantic similarity + keyword). This clearly distinguishes search_servers from siblings like get_server, list_categories, and recently_added, all of which serve different purposes.

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 provides strong context for when to use this tool: for free-text and natural-language discovery across the catalog. It also explicitly instructs to call get_server before recommending an install, which is a clear follow-up guideline. However, it does not explicitly mention when to prefer siblings like similar_to or compare, so it falls short of a 5.

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