Industry Benchmark Comparison

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

Annotations already indicate readOnlyHint, idempotentHint, and non-destructive. The description adds transparency about the data source (curated static tables, not live) and the output structure (includes industry, your_metrics, benchmarks, comparison, recommendations). This provides sufficient behavioral context beyond the 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?

The description is concise at three sentences. The first sentence front-loads the core purpose. The second sentence lists inputs clearly. The third sentence details the output structure and data nature. No extraneous information.

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 two simple parameters (one required enum, one optional enum), no output schema, and clear annotations, the description is complete. It explains inputs, output shape, and data source. No additional information is needed for an agent to use this tool effectively.

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 50% (industry has a description, platform does not). The description lists example values for industry and mentions an optional platform filter, adding meaning beyond the schema. It compensates for the missing schema description of platform by indicating its optionality and purpose.

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's purpose: compare ad performance against industry averages. It specifies the verb 'compare', the resource 'ad performance against industry averages', and the scope 'for a chosen vertical'. It is distinct from sibling tools like 'audience_insights' or 'ads_report', which serve different functions.

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 explains when to use this tool (comparing ad performance to industry benchmarks) and lists valid inputs. It also clarifies that benchmarks are curated static tables, not live market data, which helps set expectations. However, it does not explicitly state when not to use it or mention alternatives among siblings.

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