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

With no annotations provided, the description carries the full burden. It discloses the key behavioral trait: 'Returns metadata only (number, slug, title, role, score, reason, compatible_with),' clarifying that it does not return code and that follow-up via get_pattern is required. It also mentions compatibility suggestions and exclusion behavior implicitly through context.

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 focused sentences, front-loaded with the tool's purpose, then immediately clarifying the output format and next step. No wasted words; 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?

The description is complete for a recommendation tool: states what it does, how to invoke it, what it returns, and how to follow up for actual code. The input schema covers parameters well, and the description sufficiently explains return values given there is no output schema.

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 100%, so baseline is 3. The description adds value by elaborating the 'intent' parameter with examples ('industry, style, mood, technical needs') and clarifies that results include 'compatibility suggestions,' enriching what the schema alone provides.

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 provides 'intent-aware pattern recommendations' based on a building intent, and returns scored results with reasons and compatibility suggestions. It explicitly distinguishes itself from get_pattern by saying 'Call get_pattern to retrieve the actual code for any recommendation,' positioning it as a recommendation-only tool.

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 gives clear context: use it when you need scored pattern recommendations based on a descriptive intent. It also points to get_pattern for code retrieval, providing a relationship to a sibling tool. It doesn't mention exclusions or when not to use it, but the context is strong.

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