get_history_stats

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

With no annotations, the description carries the burden of behavioral disclosure. It adds useful context like calendar-quarter alignment and the type of outputs, but it does not explicitly state that the operation is read-only or mention any rate limits or error conditions. The 'Get' verb implies safety but doesn't make it explicit.

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 two sentences long, front-loaded with the verb and resource, and provides precise output details without any fluff. Every word earns its place.

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?

Since there is no output schema, the description does a good job covering the main return components and temporal bucketing. It doesn't mention edge cases like empty results or invalid appId, but it's sufficiently complete for a single-parameter read 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?

The schema fully describes the appId parameter as 'The numeric Apple track ID.' (100% coverage). The tool description adds no additional parameter-level meaning beyond restating the resource context. Baseline 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 identifies the resource (one app) and the specific outputs (per-quarter category trend with added/removed, and a sparkline of change-event counts). This distinguishes it from siblings like get_changelog that likely return raw events.

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 the tool is for aggregated history stats, but it does not explicitly contrast it with get_changelog or get_app_changelog. It provides clear context without exclusions, so it earns a 4 rather than a 5.

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