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rushikeshmore

Shopify Partner Agent

get_churn_risk

Score active merchants by churn risk using deactivation events, cancellations, and inactivity signals, returning low/medium/high levels with contributing factors.

Instructions

Score active merchants by churn risk (low/medium/high).

Args: app_id: App GID or numeric ID (required).

Heuristic signals: deactivation events, subscription cancellations, reinstall patterns, declining charges, long inactivity.

Returns: JSON string with risk summary and merchant lists grouped by risk level (high/medium/low) with contributing factors.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
app_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the full burden and does well by disclosing heuristic signals (deactivation events, subscription cancellations, etc.) and the exact return structure (JSON string with risk summary and grouped merchant lists). It does not mention side effects or permissions, but the read-only nature is implied.

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 well-structured with clear sections for purpose, args, heuristic signals, and returns. Every sentence adds value, and it is appropriately concise without extraneous detail.

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

Completeness4/5

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

Given the tool's simplicity (one parameter), the description covers the main aspects: purpose, input, behavior, and output. It does not explicitly differentiate from get_churn_analysis or get_churned_merchants, which slightly reduces completeness, but overall it is sufficiently self-contained.

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

Parameters4/5

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

Schema description coverage is 0%, and the description compensates by explaining that app_id can be 'App GID or numeric ID', adding meaning beyond the bare schema property. It clearly labels the parameter as required and gives a brief but useful type clarification.

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 starts with a clear verb and resource: 'Score active merchants by churn risk' and specifies the output levels (low/medium/high). It is specific but does not explicitly differentiate from sibling tools like get_churn_analysis or get_churned_merchants.

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?

No guidance is given on when to use this tool versus alternatives. There is no mention of suitable conditions, exclusions, or references to sibling tools. The description simply states what it does without contextual usage advice.

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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