google_ads_monitoring_cv_goal

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

With no annotations, the description fully discloses key behavioral traits: the evaluation window is hardcoded to LAST_7_DAYS, it's read-only, the bottleneck routing logic (impression when impression drops or impressions<clicks*10; CTR when CTR<2%; CVR otherwise), and the status threshold (80% of target triggers warning).

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 front-loaded with the main purpose, then provides return structure, bottleneck logic, and sibling tool references. Every sentence adds useful information without redundancy.

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 the tool and no output schema, the description fully details the return object fields, bottleneck routing, and status conditions. It also refers to sibling tools for completeness.

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 already has good descriptions (100% coverage). The description adds extra context: explains that customer_id falls back to configured credentials, and specifies that target_cv_daily is required and the status threshold behavior. It adds value beyond the 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 clearly states the tool evaluates a campaign's daily conversion rate against a target and identifies the dominant bottleneck. It specifies the return payload fields. It also distinguishes itself from sibling tools like google_ads_monitoring_cpa_goal.

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 explicitly tells when to use this tool (for CV goal evaluation), and provides alternatives: 'For CPA-target evaluation use google_ads_monitoring_cpa_goal; for the underlying composite use google_ads_performance_analyze.' This is clear guidance.

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