google_ads_cpc_detect_trend

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

With no annotations provided, the description fully carries the behavioral transparency burden. It discloses that the tool is read-only, excludes days with zero clicks from the GAQL, defines the exact thresholds for 'rising' and 'falling' (>+1% / <-1%), and details the conditional presence of change_rate_per_day_pct. It also specifies insight-triggering conditions (week-over-week surges >15%, days exceeding 2x average CPC), going far beyond basic safety annotations.

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 dense but well-structured: opening purpose, full return schema, classification rules, data exclusions, insight criteria, and alternative tools. Every sentence contributes valuable information without redundancy or fluff, making it an efficient and well-organized description.

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 tool's complexity and absence of an output schema, the description is remarkably complete. It details the exact return structure, including nested daily_data and trend objects, defines all possible direction values, explains data exclusions, and documents insight thresholds. It also provides sibling alternatives, making the tool's context fully understandable without needing additional documentation.

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 describes all three parameters with examples and guidance (e.g., period enum descriptions). Since schema coverage is 100%, the baseline is 3. The description does not add parameter-specific syntax or format details beyond what the schema provides, so it earns the baseline score.

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 opens with a specific verb and resource: 'Detect rising/falling CPC trends in a Google Ads campaign over a reporting window using daily segmentation and linear regression.' It clearly defines the tool's analytical scope and method, and distinguishes it from sibling tools by explicitly naming alternatives for device/auction investigation.

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 provides explicit guidance on when to use this tool versus related alternatives: 'For device or auction-share investigation use google_ads_device_analyze or google_ads_auction_insights_analyze.' It also states the tool is read-only and defines the thresholds that trigger insights, giving clear context for appropriate use.

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