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alopeyk_loyalty_products

Retrieve a list of loyalty products or buy one with loyalty points. Buying requires enable_ordering to be true.

Instructions

List loyalty products, or buy one — buying is gated by enable_ordering.

Persian purpose: مشاهده محصولات وفاداری یا خرید یک محصول. Requires an access_token. Listing (buy=false) maps to GET /api/v2/loyalty/customer/products/{id?}. Buying (buy=true) maps to POST /api/v2/loyalty/customer/products/{id} and spends loyalty points/credit — it requires enable_ordering=true (and read_only=false), otherwise it returns {"error": "ordering_disabled", ...} without contacting the API.

Args: product_id: Optional loyalty product id (required when buy=true). buy: When true, purchase the product (a real, gated action). instance: Configured instance to use (default when omitted).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
product_idNo
buyNo
instanceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations provided, the description fully discloses behavior: listing is GET, buying is POST, buying spends loyalty points/credit, requires enable_ordering and read_only=false, and returns error if gated. Also mentions access_token requirement.

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?

The description is well-structured with a summary, Persian purpose, technical mapping, and args. However, it is slightly verbose (e.g., Persian purpose may be redundant for an English AI agent).

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?

Given that an output schema exists, the description covers input behavior comprehensively: listing, buying, gating, and error cases. It is complete enough for an agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, yet the description explains each parameter: product_id is optional but required when buy=true, buy is a boolean defaulting to false, instance is default when omitted. This adds significant meaning beyond the schema.

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 lists or buys loyalty products, using specific verbs like 'list' and 'buy'. It distinguishes itself from siblings (e.g., alopeyk_create_order) by focusing exclusively on loyalty products.

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 explains when to list (buy=false) vs buy (buy=true), including the gating condition enable_ordering=true for buying. It does not explicitly compare with alternatives, but the domain loyalty products is well-defined.

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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