summarize_winning_patterns

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

No annotations are provided, so the description alone must convey behavioral traits. It implies a read-only analytical operation, but it never explicitly says whether it mutates data, what side effects occur, or how it accesses stored patterns. This is a significant gap for an unannotated tool.

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 a single, front-loaded sentence with no filler or redundancy. Every word earns its place, and the size is appropriate for a simple two-parameter tool.

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?

Without annotations or an output schema, and with overlapping sibling tools, the description is too thin. It does not clarify the expected return format, default behavior when parameters are omitted, or which sibling handles variant generation versus summarization. The agent can infer the domain but lacks important invocation context.

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 100%, and both top and min_score already have clear descriptions in the input schema. The tool description adds no additional parameter meaning, so the baseline score of 3 is appropriate.

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 ('Summarize') with a clear resource ('top stored swipe patterns') and names the expected outcome ('recommend ServiceHawk remix angles'). It is distinguishable from list_ad_swipes and score_ad_pattern, though it does not explicitly contrast with generate_servicehawk_variants.

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?

There is no guidance on when to use this tool versus its siblings, such as generate_servicehawk_variants or list_ad_swipes. It also does not state prerequisites like having stored patterns first, or when another tool would be more appropriate.

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