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

The annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows it's a safe read operation. The description adds value by explicitly stating the data returned (daily metrics list) and the purpose (trend analysis, reports), which goes beyond the annotations. However, it doesn't disclose details like data aggregation, timezone handling, or pagination, but given the read-only nature and no output schema, the description provides adequate context. No contradiction with 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 concise and front-loaded. It starts with the core purpose and lists key metrics, then ends with use cases. Three sentences with no redundancy, every sentence adds value. It's appropriately sized for the tool's simplicity and matches the schema coverage.

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 tool has a simple structure: 3 parameters with full schema coverage, no output schema, and annotations that cover safety. The description provides the purpose, the returned metrics, and example use cases, which is complete for an agent to decide whether to call it and set the right parameters. Nothing critical is missing for a read-only analytics tool.

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 description coverage is 100%, and the schema provides clear descriptions for each parameter (e.g., end_date, start_date with defaults, project_id as required). The description adds context by implying the date range is for daily metrics, but it doesn't add syntax or format details beyond what the schema already states. With full schema coverage, a baseline 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's purpose: fetching daily Search Console and GA4 metrics for a project, and lists specific metrics (clicks, impressions, sessions, etc.). It is distinct from sibling tools like get_top_pages or get_top_queries, which focus on specific subsets, and from compare_analytics_periods, which compares periods. However, it doesn't explicitly name those siblings or draw the contrast, so it doesn't fully differentiate.

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 states when to use this tool: 'Use for trend analysis, performance reports, comparing periods.' This gives clear context. It doesn't explicitly say when not to use it or mention alternatives, but given the clear use cases and the nature of the tool (a read-only analytics fetch), the guidance is sufficient. Sibling tools like compare_analytics_periods suggest an alternative for period comparison, but the description doesn't exclude that.

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