Get ai tracking trends

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

Annotations already establish readOnlyHint=true, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds genuinely useful data-quality context — 'original provenance, partial states, and cost uncertainty' — warning the agent that returned data may be incomplete or uncertain. However these caveats are vague (which states, which costs?) and no pagination or auth behavior is described.

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?

A single compact sentence with the scope ('project-scoped') and resource front-loaded. No wasted words, though the jargon-heavy phrasing compresses a lot of meaning into vague terms.

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?

For a 5-parameter read tool with a fully documented schema and non-destructive annotations, the description is thin: it does not clarify what a 'trend' result contains, how it differs from the history/evidence siblings, or how pagination over partial states works. Schema richness offsets some of this, but the core output concept remains unexplained.

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%, with every parameter documented in the schema (project_id, run_id, previous_run_id, limit, cursor). The description adds no parameter-level detail, so the baseline of 3 applies.

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 states a verb ('Read') and a resource ('AI tracking evidence'), but the resource does not match the tool name 'get_ai_tracking_trends' — it never mentions trends or time-series output. With siblings like get_ai_tracking_history, get_ai_tracking_run, and export_ai_tracking_evidence in the same family, the reader cannot tell what makes this tool distinct.

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?

There is no when-to-use guidance, no mention of alternatives such as get_ai_tracking_history or export_ai_tracking_evidence, and no stated preconditions. The agent must guess which AI-tracking read tool to call.

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