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imachiever

Swiggy AI Insights MCP Server

by imachiever

search_orders

Find past Swiggy orders by restaurant, cuisine, or location to analyze food habits and spending.

Instructions

Search orders by restaurant name, cuisine, or location

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results (default: 20)
queryYesSearch query (restaurant/cuisine/location)
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the search action and criteria but does not mention whether the operation is read-only, if there are any side effects, how results are sorted, or whether pagination is applied. This lack of behavioral context is a significant gap for a tool with no annotation support.

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 a single sentence that front-loads the verb and resource, and clearly communicates the searchable fields. There is no waste or redundancy—every word earns its place.

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

Completeness3/5

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

Given the tool's simplicity and the schema's thorough parameter documentation, the description provides an adequate high-level overview. However, there is no output schema, so the description should explain what the search returns (e.g., a list of orders) and any limitations (e.g., default max results). It mentions neither, leaving some ambiguity for the agent.

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?

The input schema already has 100% coverage, describing both the 'query' parameter (with the same restaurant/cuisine/location hint) and 'limit'. The description adds little beyond restating the schema's own description, so it does not elevate the baseline of 3.

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 action ('Search orders') and defines the scope by specifying search criteria: restaurant name, cuisine, or location. This differentiates it from sibling tools like get_orders (likely fetching by ID) and sync_orders (synchronization).

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

Usage Guidelines3/5

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

The description implies usage: it is a search tool with specific filters, but it does not explicitly state when to prefer it over alternatives or provide exclusions (e.g., 'use get_orders for exact ID lookups'). The context is clear enough for an agent to infer its purpose, but no direct guidance is given.

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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