get_campaign_performance_metrics

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

No annotations provided, so description carries full burden. Covers data source, row structure, row limit, truncation notice, and required environment variables. Does not detail output schema (none provided) or behavior when no filters applied, but sufficiently discloses key behavioral traits.

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 concise sentences that front-load the core purpose and gradually add detail. No filler; every sentence provides value.

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 4 optional string params and no output schema, the description covers data source, content, return structure, filtering, row cap, truncation, and environment variables. Could mention behavior with no filters, but overall complete for effective use.

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 has 0% description coverage, but description compensates by explaining that start_date, end_date, platform, and campaign_id are for filtering. However, it does not specify date formats, valid platform values, or that parameters are optional, limiting practical parameter usage guidance.

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 it queries daily campaign metrics (spend, impressions, clicks, conversions) from a unified BigQuery view across multiple platforms. It distinguishes itself from sibling tools like 'get_campaign_performance' by specifying the cross-channel, aggregated nature, though it doesn't explicitly differentiate from all similar tools.

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?

Provides direct guidance on filtering by date range, platform, or campaign_id to narrow results. Mentions the 150-row cap and advises applying tighter filters if truncation occurs. Lacks explicit when-not-to-use guidance but is adequate for typical usage.

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