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

Annotations already establish readOnlyHint=true, openWorldHint=true, and destructiveHint=false. The description adds useful behavioral detail beyond that: ranked results, human-readable match quality, and source links, plus the filter axes. No contradiction with 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?

Three tight sentences: purpose and scale in the first, filter dimensions in the second, and output behavior in the third. It is front-loaded, has no filler, and every sentence earns its place.

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?

For a 10-parameter optional search tool with an output schema, the description covers scope, filters, and return value character. It stops short of explaining filter interaction or routing among siblings, but it is sufficient for a caller to invoke the 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%, and the description reinforces the meaning of most filter parameters (capabilities, resource_type, platform, pricing, deployment, open_source, verified). However, it does not clarify 'official', 'limit', or 'query' semantics, nor how filters combine, so the description only partially compensates for the schema gaps.

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 identifies the verb 'Search' and the resource—ABCommunity's catalog of 12,000+ AI resources—while enumerating resource types and filter dimensions. It does not explicitly differentiate from siblings like find_mcp_for_task or recommend_resources, but the catalog-scale framing makes the purpose reasonably distinct.

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 implies usage: use this tool whenever you need to browse or filter the ABCommunity catalog by capabilities, type, platform, pricing, deployment, or status. However, it provides no when-not-to-use guidance or explicit alternatives, which matters given several recommendation and search siblings.

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