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

With no annotations, the description carries full behavioral burden. It clearly states the tool is read-only, scoped to the API key's organization, returns monthly/weekly data, and returns null rather than zero for unmeasurable metrics. This provides agent-relevant behavioral guarantees without relying on 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 main description is a single dense sentence with a long metric list, but it front-loads the core purpose and contains no filler. Each clause adds useful information, though the length makes it slightly harder to parse quickly.

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 no output schema, no annotations, and six parameters with 0% schema coverage, so the description must do substantial work. It covers the metric set, read-only nature, scope, and null semantics, but leaves format variants, date range semantics, and orgSlug/API key relationship underspecified.

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 0%, but the description does not explain key parameters: what format enum values 'summary', 'full', or 'ev' mean, how from/to/weeks interact, or why orgSlug is required if output is scoped to the API key org. Parameter names are somewhat self-explanatory, but the description adds almost no parameter-level clarity.

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?

Description names a specific resource (adoption and switching evidence), a granularity (month/week), and a long concrete metric list, so an agent knows exactly what this tool computes. It also frames the query intent ('is this org actually using the product or still on its spreadsheet'), which distinguishes it from sibling report_* tools.

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 gives an explicit use case: answer whether an organization is actually using the product. It does not explicitly explain when not to use it or point to alternatives, but the stated intent is clear enough for selection.

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