list_storesList every connected store/marketplace account (Amazon, Shopify, Flipkart, Snapdeal, Meesho, Myntra, JioMart, Ajio, offline) with its display name, country/currency, and order count in the last 30 days.
| Name | Required | Description | Default |
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No arguments | |||
| Name | Required | Description | Default |
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No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already provide readOnlyHint=true and destructiveHint=false, so the read-only nature is covered. The description adds valuable behavioral context by stating it lists 'every' connected store, enumerating marketplace types, and specifying the 30-day order count window. This goes beyond the annotations but omits details like possible pagination or ordering behavior.
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 a single sentence that packs a lot of useful detail without filler words. It is front-loaded with the action and resource, but the long enumeration of platforms and fields creates a dense sentence that could be structurally streamlined while still being concise.
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 presence of an output schema and zero parameters, the description covers the essential behavioral scope: what stores are included, what fields are returned, and the timeframe. The tool is straightforward, and the description combined with annotations and output schema provides a complete picture.
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 tool has zero parameters, so the schema trivially covers everything. According to the rubric, the baseline for 0 params is 4, and the description does not need to compensate for missing parameter information. It effectively explains what the tool returns, which is sufficient.
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 uses a specific verb ('List') and resource ('connected store/marketplace account'), enumerates the supported platforms (Amazon, Shopify, Flipkart, etc.), and specifies the exact return fields (display name, country/currency, order count in last 30 days). This clearly distinguishes it from generic siblings like list_integrations and leaves no ambiguity about its function.
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 does not explicitly state when to prefer this tool over alternatives, nor does it mention any exclusions. Usage is implied from the name and the clear scope, but there is no comparison to similarly named list_* tools or guidance on when a different tool (e.g., list_integrations) would be more appropriate.
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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Most tools target distinct data points (e.g., get_analytics_summary vs get_brand_score). However, 'search' and 'search_catalog' have overlapping functionality and could cause confusion, and 'fetch' is a helper tied to 'search', adding minor ambiguity.
The majority use consistent verb_noun snake_case (e.g., get_inventory, list_stores). Exceptions like 'fetch' and 'search' (without object) break the pattern, but they are few.
43 tools is excessive for a data-retrieval-only API. Many get_* and search_* tools could be consolidated (e.g., search_catalog, search_inventory, search_orders are similar). The large number will overwhelm an agent.
The tool set is entirely read-only (get, search, list, fetch). There are no create, update, or delete tools, which is a critical gap for managing e-commerce operations. Agents can only view data, not act on it.