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Search returns

search_returns
Read-only

Find specific returns across all connected channels. query matches a return ID or reverse-shipment tracking (AWB) number (substring). Filter by channel, return bucket, received status, and date range. Each result is a full return record (reason, qty, refund, dates). Money in minor units.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax records to return (1-25, default 15).
queryNoReturn ID or AWB / tracking number to search for.
sinceNoISO date — only returns initiated on/after this.
untilNoISO date — only returns initiated on/before this.
bucketNoFilter by return category.
channelNoRestrict to one channel code.
receivedNotrue = already received at warehouse; false = awaiting receipt.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsNoMatched records.
limitNo
totalNoTotal matches before paging.
offsetNo
messageNo
availableNo

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral context: query matches substrings of return ID or tracking number, each result is a full return record with fields like reason, qty, refund, and dates, and money is in minor units. This goes beyond the safety profile and helps the agent understand output nuances.

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 four sentences, front-loaded with the main purpose. Each sentence adds distinct information: purpose, query matching, filters, and result format. There is no redundancy or filler, making it highly concise and well-structured.

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 complexity (7 optional parameters) and the presence of an output schema and annotations, the description covers the essential behavior: substring matching, filters, and result contents. It does not explicitly clarify behavior when query is omitted (whether it returns all returns), which is a minor gap, but the overall context is sufficient for an agent to use the tool correctly.

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?

The schema covers 100% of parameters with descriptions, so the baseline is 3. The description adds meaning by specifying that query matches substrings and that amounts are in minor units, which are not present in the schema. It also summarizes the core filter dimensions (channel, bucket, received status, date range), reinforcing the schema.

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

Purpose5/5

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

The description clearly states the tool's purpose: 'Find specific returns across all connected channels.' It uses a specific verb and resource, and distinguishes itself from sibling tools like search_orders by focusing on returns. It also previews filtering capabilities and result contents, making it easy to understand what the tool does.

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

Usage Guidelines4/5

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

The description gives clear context that this tool is for finding specific return records with filters by channel, bucket, received status, and date range. It implies when to use this tool (when you need return details) but does not explicitly name alternatives or exclusions, so it falls short of a 5.

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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TDQS

A3.5/5.0
Disambiguation4/5

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.

Naming Consistency4/5

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.

Tool Count2/5

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.

Completeness2/5

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.

Resources