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sstepanovvl

mcp_canadiantire

by sstepanovvl

Check Canadian Tire store availability for a SKU

ct_store_availability

Check in-store stock of a Canadian Tire SKU across nearby stores. Returns store details and availability sorted by stock status and distance.

Instructions

Check in-store stock of a Canadian Tire SKU across nearby stores. Returns, per store: store name, address, phone, coordinates, distance, in-store stock quantity, shelf/aisle location, and pickup availability — sorted in-stock first, then nearest. Also reports online (Corporate) stock. Use to answer 'which store has this in stock near me'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skuYesProduct code, e.g. '0542448P'.
postalCodeNoPostal code, e.g. 'M5V 2T6'; nearby stores are taken around it (overrides storeId).
storeIdNoReference store; nearby stores are taken around it. Default 676.
langNoResponse language. Default 'en'.
limitNoMax number of stores to check (1-25). Default 10.
Behavior4/5

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

With no annotations provided, the description details the tool's behavior: returns sorted list, includes online stock, and lists output fields. It does not disclose potential side effects or authorization needs, but for a read-only tool this is sufficient.

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 sentences, front-loaded with the main action and output summary, no wasted words. Efficient and clear.

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?

The description explains output structure and usage context well. Missing details on error handling or data freshness, but overall adequate given no output schema.

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 coverage is 100% with good parameter descriptions. The description adds overall context (e.g., sorting, online stock) but does not significantly enhance individual parameter meaning beyond the schema, maintaining baseline.

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 checks in-store stock of a Canadian Tire SKU across nearby stores, listing returned fields and sorting. It directly addresses a user question, distinguishing itself from sibling tools like ct_product, ct_search, and ct_stores.

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?

The description explicitly says to use it to answer 'which store has this in stock near me', providing clear context. However, it does not mention when not to use it or compare with alternatives, missing some guidance against sibling tools.

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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