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rushikeshmore

Shopify Partner Agent

get_transactions

Retrieve revenue transactions from Shopify Partner accounts, filtering by app, date range, or transaction type for earnings analysis.

Instructions

Get revenue transactions from your Shopify Partner account.

Args: app_id: Filter by specific app (optional). date_from: Start date YYYY-MM-DD (optional). date_to: End date YYYY-MM-DD (optional). transaction_types: Comma-separated filter. Types: APP_SUBSCRIPTION_SALE, APP_USAGE_SALE, APP_ONE_TIME_SALE, APP_SALE_ADJUSTMENT, APP_SALE_CREDIT, SERVICE_SALE, REFERRAL_TRANSACTION limit: Max transactions (default 100).

Returns: JSON string with keys: transactions (list with type, amount, app, shop, date), count.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
app_idNo
date_toNo
date_fromNo
transaction_typesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses the return format and transaction types, which is helpful. But it doesn't mention behavior like whether filters are required, whether pagination is supported beyond a limit, or any error conditions. Still, for a read-only tool, the core behavior is clear.

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 structured with Args and Returns sections, front-loaded with the purpose. It includes necessary detail without fluff. The transaction type list is long but required for correct usage.

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?

The description covers the main purpose, all parameters, and the return structure. It also includes a count in the response. Given the moderate complexity and the presence of an output schema, this is adequate, though it doesn't address potential edge cases or pagination beyond the limit parameter.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate. It does so thoroughly: each parameter (app_id, date_from, date_to, transaction_types, limit) gets an explanation, including the accepted values for transaction_types and the default for limit. This exceeds the schema's minimal info.

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 'Get revenue transactions from your Shopify Partner account,' naming a specific verb and resource. However, it does not explicitly differentiate this tool from sibling tools like get_revenue_summary or get_payout_report, so it stops short of a 5.

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 instead of alternatives. It lists arguments but does not state the scenario this tool is best suited for, or any exclusions. There is no 'use X instead' type of instruction.

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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