google_ads_trend_analysis

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

No annotations are present, so the description must carry the burden. It mentions it analyzes and provides daily data, but does not disclose whether it is read-only, affects any state, or has any side effects. Given the lack of annotations, the description provides some behavioral context but is incomplete.

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 bullet points, an Args section, Returns, and an Example. It is concise and front-loads the main purpose. Every sentence adds value, though the Returns section could be slightly more detailed.

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?

The output schema exists, but the description only vaguely mentions 'Trend analysis with anomaly detection'. More detail on output structure would improve completeness. Additionally, with no annotations, the description should cover behavioral traits more thoroughly. Overall adequate but with gaps.

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 0%, so the description compensates well by providing clear, meaningful descriptions for each parameter: customer_id format, campaign_id's default scope, and lookback_days range. This adds significant value beyond the schema's bare types and defaults.

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 analyzes performance trends and detects anomalies, listing specific outputs like cost trends, conversion trends, and anomalous days. This distinguishes it from other google_ads_* performance tools that focus on static summaries or comparisons.

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 implies usage for trend analysis but does not explicitly state when to use this tool versus alternatives like google_ads_performance_insights or google_ads_wasted_spend_analysis. No exclusion criteria or context is provided.

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