RFM Analysis

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds behavioral context beyond annotations, such as data source behavior ('auto' resolves to HubSpot or sample) and industry presets. No contradictions.

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 concise and well-structured with a clear summary and bullet-pointed args. It avoids verbosity but could be slightly more compact by removing minor redundancy (e.g., repeating 'JSON with...').

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?

Given the tool's moderate complexity and the presence of an output schema (as per context), the description covers inputs, behavior, and output structure. It explains data source options and industry presets adequately, though it could mention that the output schema provides full structure.

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 input schema has 0% description coverage, providing only type and default. The description compensates fully by detailing the meaning and options for both 'source' and 'industry_preset' parameters, adding significant value.

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 it runs RFM analysis, scores clients based on purchase behavior, segments into 11 categories, and extracts ICP patterns. It distinguishes from sibling tools ('qualify' and 'score_pipeline_health') by focusing specifically on RFM segmentation.

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 implicitly indicates usage (when you need RFM analysis), but it does not explicitly state when to use this tool over alternatives or provide exclusion criteria. The context is clear but lacks comparative guidance.

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