get_visibility_history

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds useful scoping detail (per-engine breakdown, time-series nature) beyond the schema. However, it doesn't describe pagination or the time-series return structure, though the output schema exists to handle that, keeping the bar lower. A 3 is appropriate given annotations carry the safety burden.

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 core description is efficient—a single purpose sentence followed by usage examples. The example queries earn their place by providing concrete trigger patterns. Slightly padded with three near-synonymous example questions, but all serve the same differentiation purpose, so minor deduction only.

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?

Tool complexity is moderate (3 params, 1 enum, output schema present). The description covers the purpose, per-engine breakdown, and temporal use cases. The output schema handles return-value documentation, so the description doesn't need to. Could add a note about data freshness or range limits, but days min/max are already in the schema.

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%, so all three parameters (days, brand_id, granularity) are documented in the schema. The description adds the temporal framing ('growing or shrinking', 'trend') but doesn't add syntax or format details beyond what the schema already provides. Baseline 3 is correct when schema does the heavy lifting.

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?

Specific verb+resource+scope: 'get' the time-series history of a brand's AI visibility score, broken down per engine. It clearly distinguishes from siblings like check_visibility (single-point check) and compare_competitors, and explicitly states the per-engine breakdown which adds specificity.

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?

Provides explicit example queries that map to this tool ('how has my AI visibility changed over time?', 'is my visibility growing or shrinking?', 'show me the trend for the last month'). This gives agents concrete trigger patterns and clearly implies when to use it versus the sibling check_visibility tool.

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