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

With no annotations provided, the description fully carries the behavioral disclosure burden and does so thoroughly. It discloses that campaigns are 'ALWAYS created PAUSED', that the ad links to the store listing automatically with no URL input, that no app ownership is required, that v1 only optimizes for INSTALLS, and that missing conversion tracking returns a warning. It also calls out the 50x target_cpi budget recommendation and the dry_run validation behavior.

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 every sentence earns its place: core behavior, targeting, budget semantics, text constraints, media options, unsupported goals, warnings, dry-run workflow, and sibling routing. The most decision-critical facts are front-loaded ('ONE atomic request', 'ALWAYS created PAUSED', 'no URL input, ever').

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 the complexity of this tool and the absence of annotations and output schema, the description is remarkably complete. It covers prerequisites, required and optional inputs, validation behavior, unsupported features, warnings to relay, and exact alternatives. An agent has all context needed to select, invoke, and sequence this 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 only 29%, so the description must compensate — and it does. It explains app_id formats for Android and iOS, clarifies target_cpi and daily_budget are plain numbers in account currency rather than micros, points media asset IDs to adsap_google_upload_asset, references adsap_google_search_geo_targets for location IDs, and specifies that ad_account_id is a bare 10-digit customer ID. This adds substantial meaning beyond the raw schema.

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 states a specific verb and resource: 'Create a complete Google App campaign in ONE atomic request' and enumerates exactly what is included (budget, campaign, targeting, ad group, ad). It also differentiates from sibling tools by clarifying that this is for Google App campaigns with app_link auto-generated, and explicitly names alternatives for website and Meta campaigns.

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 gives explicit when-to-use guidance: 'App campaigns promote a mobile app across Google Search, Google Play, YouTube, Discover and the Display Network.' It also provides clear exclusions and alternatives: 'For website campaigns use adsap_google_create_search_campaign / adsap_google_create_pmax_campaign; for Meta app ads use adsap_create_campaign with an app objective.' The recommended dry_run-first workflow is also actionable guidance.

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