google_ads_upload_offline_conversions

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

No annotations are provided, so the description carries full behavioral disclosure burden. It explains that this is a write operation requiring GCLID, details parameter format, and mentions a return message. However, it lacks information on limitations like maximum batch size, rate limits, error handling, or idempotency, which are gaps given no 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 well-structured with a clear header, bulleted Args, Returns, and an example. It is concise with no redundant sentences; every part adds value, including the tip about GCLID capture. The front-loaded purpose is immediately actionable.

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 tool's complexity (3 params, one nested object), the description covers parameter meanings, required fields, format, and return value. An output schema exists but is not shown; the description mentions return is a success message with count, which is sufficient. Sibling tools exist, but the description provides enough context for correct usage. Minor gaps in behavioral transparency prevent a 5.

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?

The input schema has 0% description coverage, but the description adds significant meaning: customer_id format (no hyphens), conversion_action_id requirement (IMPORT origin), and conversions as a list of dicts with required fields (gclid, conversion_date_time) and optional fields (conversion_value, currency_code), plus date format details. This fully compensates for the schema's lack of descriptions.

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: uploading offline conversion data (CRM conversions, phone orders, store visits) that originated from Google Ads clicks. It distinguishes from siblings by specifying the use of GCLID and offline conversions, differentiating it from other upload tools like upload_call_conversions or upload_customer_match.

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 provides clear guidance on when to use the tool: 'Upload offline conversion data' and 'import conversions that happen offline but originated from Google Ads clicks.' It mentions the prerequisite of having GCLID. However, it does not explicitly state when not to use it or compare to alternative tools among siblings, though the context implies differentiation.

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