google_ads_campaigns_diagnose

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

States 'Read-only — does not change anything' and describes the output (ordered list of issues with descriptions and hints). Without annotations, this adequately discloses behavior, though it omits error conditions or rate limits.

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 sentences: purpose/output, read-only note, usage advice. No unnecessary words, front-loaded with key information.

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 no output schema or annotations, the description provides sufficient context: what it does, what it returns, when to use it. Slight lack of detail on output format, but still complete for agent decision-making.

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?

Input schema covers both parameters with 100% description coverage (customer_id fallback and campaign_id required). The description does not add meaning beyond the schema, so baseline score of 3 is appropriate.

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 diagnoses why a campaign is not serving or under-delivering, using serving_status, primary_status, and reasons. It differentiates from sibling tools like google_ads_keywords_diagnose by focusing on campaigns and returning an ordered issue list with remediation hints.

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?

Explicitly advises to use before pulling raw performance reports to narrow the problem space. Lacks explicit comparison to other diagnostic tools like analysis_anomalies_check or health_check_all, but the guidance is clear and actionable.

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