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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It explains that results are filtered by default (quality and risk) and that scores are evidence, not endorsements. This adds context beyond the schema, though it omits details like read-only nature, pagination, or response structure. Still, it provides useful behavioral traits.

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 three sentences long, front-loading the core purpose and then providing key behavioral details. Every sentence adds value: the first defines scope, the second explains ranking, the third specifies default filters. No fluff or repetition.

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 lack of an output schema and annotations, the description could be more complete. It does not describe the return format (e.g., fields, pagination, total count) or mention any rate limits. While it covers the search behavior and defaults, it leaves gaps that an agent would need to infer or test.

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 description coverage is 80%, so the schema already documents most parameters. The description adds overall context about ranking and default filtering, which indirectly clarifies the query parameter's role. However, it does not detail individual parameter usage beyond what the schema provides. For the 'limit' and 'platform' parameters, no extra meaning is added. Score at baseline.

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 it performs full-text search over the Skill of Skills directory, specifying the types of resources included (AI coding skills, plugins, MCP servers across multiple platforms). It uses a specific verb-resource pair ('search' over 'Skill of Skills directory') and naturally distinguishes itself from sibling tools like get_collection or compare_tools.

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 explicit context about default filters (quality ≥ 40, risk below high) and ranking (quality-first, not popularity). While it doesn't explicitly state when not to use this tool or name alternatives, it gives clear guidance on when the tool will return results, aiding the agent in understanding invocation triggers.

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