x_ads_reachCalculate unique reach and average frequency for ad campaigns within a 7-day window, providing audience size insight beyond raw impressions.
Unique reach + average frequency for campaigns. Window ≤ 7 days, whole-hour ISO 8601. Impressions cannot tell you this.
| Name | Required | Description | Default |
|---|---|---|---|
| end_time | Yes | ||
| account_id | Yes | Ads API account id from x_ads_list_accounts, e.g. 18ce55v2od2 | |
| start_time | Yes | ||
| campaign_ids | Yes |
Changes observed during successful MCP inspections.
v0.2.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare read-only and open-world behavior, so the description does not need to restate safety. It adds useful constraints about the accepted time window and timestamp format, but it does not disclose rate limits, aggregation behavior, or error cases. This is adequate but not rich.
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?
Three short sentences, with the core metric front-loaded and constraints following. Every sentence adds information; there is no filler or redundant restatement of the title.
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 4-required-parameter read-only analytics tool with no output schema, the description plus schema covers account_id, time constraints, resource, and the requested metrics. Still, it leaves out return-shape/aggregation details and campaign_id validation, so an agent has to infer some behavior.
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 coverage is only 25% (account_id alone), and the description compensates partially by explaining start/end_time must be whole-hour ISO 8601 and within a 7-day window. It adds no guidance on campaign_ids semantics beyond what the schema's name and maxItems imply, so the low-coverage burden is not fully met.
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 names a specific verb/outcome ('Unique reach + average frequency') and a specific resource ('campaigns'), making it clear this is an analytics read for campaigns. It also differentiates itself from impression-based analytics ('Impressions cannot tell you this'), so an agent can tell it apart from generic analytics siblings.
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 provides concrete invocation constraints (window ≤ 7 days, whole-hour ISO 8601 timestamps) and an implied use case for reach/frequency rather than impressions. However, it never names an alternative tool or states explicit when-not-to-use conditions, leaving some routing to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.