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aiva_get_rfm_segments

Analyze customer RFM segments to identify recency, frequency, and monetary value patterns with counts and trends for data-driven marketing decisions.

Instructions

Get RFM (Recency, Frequency, Monetary) segment breakdown with customer counts and trends.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateRangeNo30d
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions what the tool does but does not disclose any behavioral traits such as whether it's a read-only operation, potential rate limits, authentication needs, or error handling. For a tool with no annotations, this is inadequate, as it leaves the agent unaware of important operational aspects beyond the basic function.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence: 'Get RFM (Recency, Frequency, Monetary) segment breakdown with customer counts and trends.' It is front-loaded with the core purpose and includes essential details without unnecessary words. Every part of the sentence adds value, making it highly efficient and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (involving RFM analysis with trends), no annotations, no output schema, and low parameter schema coverage, the description is incomplete. It does not explain the return format, potential limitations, or how the 'trends' are presented, leaving the agent with insufficient context to fully understand the tool's behavior and output. This is a notable gap for a tool that likely returns structured data.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has one parameter ('dateRange') with an enum and default value, but schema description coverage is 0%, meaning the schema lacks descriptions. The description does not add any parameter-specific information beyond implying a date range is involved ('segment breakdown'), but it does not explain the parameter's role, the enum values, or how it affects the output. With low schema coverage, the description fails to compensate adequately, resulting in a baseline score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get RFM (Recency, Frequency, Monetary) segment breakdown with customer counts and trends.' It specifies the verb ('Get'), resource ('RFM segment breakdown'), and output details ('customer counts and trends'), which is specific and informative. However, it does not explicitly differentiate from sibling tools like 'aiva_get_churn_risk' or 'aiva_get_customer', which might also involve customer data analysis, so it falls short of a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It does not mention any context, prerequisites, or exclusions, and with sibling tools like 'aiva_get_churn_risk' and 'aiva_search_customers' that might overlap in customer analytics, the lack of differentiation leaves the agent without clear usage instructions. This is a significant gap in helping the agent select the right tool.

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

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