suggest_pattern

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

With no annotations, the description carries the behavioral disclosure burden. It discloses the response format (up to 3 ranked suggestions with confidence scores), which covers the core behavior. It does not address failure modes, but for a simple suggestion tool this is adequate.

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 efficient sentences with no redundancy. It front-loads the core purpose and includes usage context. Every word 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 covers the essential context: input, output, and when to use. Since there is no output schema, it provides necessary return information (ranked suggestions with confidence). Minor gaps like no-suggestion behavior are not critical for this 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 provides 100% coverage of both parameters with clear descriptions. The tool description adds no additional parameter-level semantics beyond the schema, so the baseline of 3 applies.

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 uses a specific verb ('Map') and clearly identifies the input (problem description) and output (design pattern name(s)), including result limit and confidence scores. It does not explicitly differentiate from the sibling tool get_template, so it misses the top score.

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?

Explicitly states when to call this tool ('when you know the problem but not which pattern to apply'), giving clear context. However, it does not mention alternatives or when not to use it, so it doesn't fully earn a 5.

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