Get analytics

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

Annotations already declare readOnlyHint and openWorldHint, so the description adds value by disclosing concrete behavioral constraints: the 7-day range limit, whole-hour ISO 8601 time format, default granularity (TOTAL) and metric_groups (ENGAGEMENT,BILLING), fixed placement ALL_ON_TWITTER, and spend unit conversion (billed_charge_local_micro / 1,000,000). These go beyond the annotations without contradicting them.

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, dense paragraph that leads with the core purpose and then lists essential constraints in a logical order. There is no fluff or repetition; every sentence carries useful operational detail, making it appropriately sized and front-loaded.

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?

For a tool with 7 parameters, 5 required, and no output schema, the description covers many constraints but misses key operational context. It does not state what the response format looks like (since there is no output schema), nor does it explicitly assert that entity_ids must correspond to the chosen entity type (e.g., campaign IDs for CAMPAIGN). The placement note is cryptic and unexplained. While it handles many edge cases, an agent might still lack enough to invoke it with full confidence.

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?

With schema description coverage at only 14%, the description compensates meaningfully. It explains granularity (TOTAL/DAY/HOUR), metric_groups defaults, placement constraint, and spend conversion. However, it does not explicitly define entity_ids semantics (beyond being IDs), nor does it clarify the relationship between entity type and the IDs, leaving some ambiguity. Still, it adds substantial meaning to parameters that the schema does not document.

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 opens with a clear verb and resource scope: 'Sync stats for up to 20 campaigns, ad groups, or ads.' This sets it apart from sibling tools that create, update, or list entities. The title 'Get analytics' reinforces the retrieval purpose, and the scoping to three entity types is specific and 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?

The description does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions. The purpose is implied by the name and scope, but there is no explicit guidance such as 'use this for analytics metrics rather than list calls.' It mentions constraints (e.g., ≤7 days) but not usage context relative to siblings.

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