hcp_prescribing_trend_by_segment

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

With no annotations provided, the description carries the full behavioral burden. It discloses the key behavioral output: two data categories, segment_rollup and hcp_quarterly, and that the tool can identify declining/growing HCPs. It could add notes on data availability or limitations, but for a read-only reporting tool the main behavior is clearly communicated.

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?

Two sentences with no filler. The first sentence front-loads the core function and output structure, and the second provides actionable guidance. Every clause 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?

For a tool with no output schema and no annotations, the description names both output groups and maps them to use cases, which is the essential contextual information. It is slightly light on edge-case behavior such as no-data results or how quarters_back affects the returned rows, but the core usage is complete.

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 description adds context matching brand_name, region, and specialty, and the word 'Quarterly' hints at quarters_back. However, it does not explicitly explain quarters_back semantics or the meaning of the region values; with schema coverage at 50%, the description only partially compensates for the undocumented parameters.

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 computes a quarterly prescribing trend for one product, broken out by region and specialty, with per-HCP drill-down rows. This is a specific, identifiable purpose. It does not explicitly distinguish itself from the similarly named sibling hcp_prescribing_trends, so it stops just short of full sibling differentiation.

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 explicit within-tool usage guidance: use segment_rollup for side-by-side region/specialty comparison and hcp_quarterly to find declining/growing HCPs. This is clear analytical context. However, it does not state when to choose this tool over sibling alternatives or when not to use it.

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