zobrx

Q-Radar SKU history

get_qradar_sku_history

Read-only

Time-series of shelf evaluations for one master product across pincodes and dark-stores in the window — risk score, lever scores, in-stock state, inventory, and price per observation. Get the master id from list_qradar_skus.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "masterId": "<masterId>"
    },
    "name": "get_qradar_sku_history"
  }
}

Input Schema

Name	Required	Description
`masterId`	Yes	Master product id.
`dateRange`	No	Lookback window (default last_7d).
`platforms`	No	Comma-separated quick-commerce channel codes (e.g. blinkit,zepto,instamart). Omit for all.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

AddedJun 19, 2026

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 and destructiveHint=false. The description adds behavioral context by detailing the data granularity (pincodes, dark-stores) and included metrics (risk score, lever scores, inventory, price), going beyond the annotations without contradicting them.

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?

Two tightly packed sentences, no filler. The first defines scope and outputs; the second gives lineage. Every word earns its place.

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?

With an output schema present and all parameters documented, the description sufficiently covers purpose, scope, and prerequisite. No critical information is missing for selecting and invoking the tool.

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 100%, so baseline is 3. The description adds meaning by clarifying that masterId refers to a single product and by directing users to list_qradar_skus for the value, which is helpful beyond the schema's simple field descriptions.

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 specifies a 'time-series of shelf evaluations for one master product across pincodes and dark-stores', listing concrete metrics. This clearly distinguishes it from sibling tools like get_qradar_overview or list_qradar_skus, and even explains how to obtain the required master id.

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?

It provides clear context for when to use the tool (time-series history for one product) and explicitly points to list_qradar_skus for obtaining the master id. It does not mention exclusions or alternatives, but the usage context is evident.

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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