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

Beyond the readOnly/idempotent annotations, it discloses deterministic server-side computation ('nothing re-derived, nothing estimated'), list truncation with marked omitted counts, bounded weekly series, and the requirement of the caller's own account with Audience 360 connected. No contradictions with 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 dense but well-structured: starts with core purpose, then usage directive, then section breakdown, then behavioral notes. It is long but every sentence contributes critical context (contents, truncation, filtering, auth). Could be slightly tightened, but not wasteful.

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?

With 8 parameters and no output schema, the description compensates thoroughly: it enumerates all section contents, mentions the output format briefly, notes truncation behavior, gives filtering advice, and points to get_app_context for the data map. This gives an agent enough to select and invoke the tool correctly.

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% (baseline 3). The description adds value by explaining what each report section contains and explicitly advising to filter with range/channel/countries to sharpen the question. It maps sections to interpretation use cases, going beyond the schema's parameter-level definitions.

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 identifies this as an audience report over the caller's own connected Google Search Console + GA4 + social connector data, computed server-side. It explicitly lists the eight report sections and distinguishes it from rebuilding KPIs from raw connector tables, making its purpose unambiguous.

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?

It states 'Use this FIRST for any interpretation question about a user's traffic/audience' with concrete examples, and explicitly recommend it over the alternative of rebuilding KPIs from raw connector tables. It also gives guidance on choosing only needed sections and using filters, plus the prerequisite of an autario account with Audience 360 connected.

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