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snapp-mcp

by sepehr071
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Python
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Find cheapest dish

food_find_cheapest
Read-onlyIdempotent

Compare nearby open restaurant menus and FoodParty deals to find a cheaper total price for a dish, including discounts, packaging, and delivery fees.

Instructions

Find the cheapest way to get a dish: scans menus of nearby open restaurants plus FoodParty deals.

Use for the lowest total price of X. Ranks by food price after discount + packaging + delivery fee; check min_order, a cheap dish may not reach the minimum basket. Slower than food_search.

Input Schema

NameRequiredDescriptionDefault
latYesDelivery point latitude.
longYesDelivery point longitude.
limitNoMax dishes.
queryYesDish word, e.g. 'پیتزا'.
max_restaurantsNoOpen restaurants' menus to scan (more = slower).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed13 schema fields changedv0.2.0
    • changedInput schema / properties / lat / description
      Previous value: -"Latitude of the delivery point (Iran: ~25 to ~40)."New value: +"Delivery point latitude."
    • removedInput schema / properties / lat / title
      Removed value: -"Lat"
    • changedInput schema / properties / limit / default
      Previous value: -20New value: +10
    • changedInput schema / properties / limit / description
      Previous value: -"Max dishes to return."New value: +"Max dishes."
    • removedInput schema / properties / limit / title
      Removed value: -"Limit"
    • changedInput schema / properties / long / description
      Previous value: -"Longitude of the delivery point (Iran: ~44 to ~63)."New value: +"Delivery point longitude."
    • removedInput schema / properties / long / title
      Removed value: -"Long"
    • changedInput schema / properties / max_restaurants / description
      Previous value: -"How many open restaurants' menus to scan (more = slower, more complete)."New value: +"Open restaurants' menus to scan (more = slower)."
    • removedInput schema / properties / max_restaurants / title
      Removed value: -"Max Restaurants"
    • changedInput schema / properties / query / description
      Previous value: -"Dish or food word, Persian works best, e.g. 'پیتزا', 'کباب'."New value: +"Dish word, e.g. 'پیتزا'."
    • removedInput schema / properties / query / title
      Removed value: -"Query"
    • removedInput schema / title
      Removed value: -"food_find_cheapestArguments"
    • changedOutput schema / (root)
      Previous value: -{
-  "additionalProperties": true,
-  "title": "food_find_cheapestDictOutput",
-  "type": "object"
-}New value: +null
  2. First observedv0.1.1

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, open-world, non-destructive, so the safety bar is low. The description adds real behavioral value beyond that: the ranking formula (food price after discount + packaging + delivery fee), the min_order caveat, and the latency trade-off versus food_search.

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?

Three tight sentences, front-loaded with what the tool does, followed by usage, then the caveat and trade-off. Nothing is padding.

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?

There is no output schema, but the description tells the agent what it effectively returns (dishes ranked by total landed price) and warns about the min_order edge case. It is complete enough to call correctly, though the shape of results and result count behavior are only implied.

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 lat, long, query, limit, and max_restaurants are already documented with meaning, defaults, and bounds. The description explains the cost model that drives ranking but adds no parameter-specific syntax or format beyond the schema, so baseline 3 applies.

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 (find the cheapest way to get a dish) plus the exact mechanism (scans nearby open restaurant menus and FoodParty deals). An agent can distinguish this from food_search and food_party_deals 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 Guidelines5/5

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

Explicitly says when to use it ("Use for the lowest total price of X") and routes the agent away from the sibling by contrast ("Slower than food_search"). It also gives a concrete precondition to check: min_order, since a cheap dish may not reach the basket minimum.

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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