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Glama

get_order_history

Retrieve recent Blinkit order history with dates, totals, statuses, and purchased items to see past orders and infer recurring purchases when building a new order. Set count to limit results.

Instructions

Fetch recent Blinkit order history in an LLM-friendly format: for each order, its date, total, status, and the items bought (name, variant, quantity, price). Use this to see what the user has ordered before and infer recurring purchases when building an order. count sets how many recent orders to fetch (default 10).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.1.0

TDQS

A4.1/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. "Fetch" implies a read-only operation and the returned fields are spelled out, which is useful, but prerequisites are unstated (e.g., whether login/OTP or a set location is required first) and nothing is said about behavior when the user has no orders.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, front-loaded with the retrieval action and its return payload, followed by usage and then the parameter. Efficient overall, though the return-field enumeration slightly overlaps the existing output schema.

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?

An output schema exists, so return values need not be detailed, and the description still covers purpose, usage, and the lone parameter. What remains thin is the ambient behavior of a multi-step ordering flow (auth/location prerequisites) that the description never mentions.

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 0%, so the description must compensate for the single `count` parameter, and it does: "`count` sets how many recent orders to fetch (default 10)." It omits any upper bound or pagination behavior, which leaves a small gap.

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?

States a specific verb and resource ("Fetch recent Blinkit order history") and enumerates what comes back per order (date, total, status, items with name/variant/quantity/price). No sibling (search, check_cart, checkout, etc.) overlaps with order history, so an agent can distinguish it without opening any schema.

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?

Provides an explicit usage condition: "Use this to see what the user has ordered before and infer recurring purchases when building an order." It does not state when-not-to-use or name an alternative, but no sibling competes for this purpose, so context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.