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Search orders

search_orders
Read-only

Find specific orders across all connected channels. query matches an order ID, line-item ID, or SKU (substring). Filter by channel, attribution state, and date range. Money fields are in minor units (paise for INR) — convert to ₹. Use get_order for full detail on one order.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax records to return (1-25, default 15).
queryNoOrder ID / line-item ID / SKU to search for.
sinceNoISO date — only orders created on/after this.
untilNoISO date — only orders created on/before this.
channelNoRestrict to one channel code (e.g. amazon, flipkart).
attributionStateNoFilter by order lifecycle state.

Output Schema

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

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, so the safety profile is known. The description adds valuable behavioral context beyond annotations: it notes that money fields are in minor units (paise for INR) and must be converted to ₹, and it states the search operates 'across all connected channels.' This goes beyond the basic read-only nature.

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 three sentences, front-loaded with purpose, then query semantics, money unit caveat, and alternative tool referral. Every sentence earns its place with no redundancy or filler.

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

Completeness5/5

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

Given the tool has an output schema and no required parameters, the description fully covers selection and invocation: purpose, query syntax, filters, unit conversion, and an alternative (get_order). Nothing essential is missing for a read-only search tool.

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?

Schema description coverage is 100%, so the parameters are well-documented. The description reiterates what query matches and mentions filters, but does not add additional parameter-level semantics beyond the schema. It does not introduce nuances like default behavior or formatting beyond what the schema already provides.

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 opens with a specific verb and resource: 'Find specific orders across all connected channels.' It clearly states what the tool does and distinguishes it from siblings by noting the cross-channel scope and explicitly referencing get_order for full order detail.

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

Usage Guidelines5/5

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

The description gives explicit usage guidance: it explains the query matches an order ID, line-item ID, or SKU, and lists available filters. It also directly instructs to 'Use get_order for full detail on one order,' providing a clear alternative for when this search tool is not 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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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