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Get a store's discount codes and deals

get_store_offers
Read-onlyIdempotent

Every live discount code and deal Vouchernaut lists for one UK store, in the order its store page shows them: what each saves, its terms and end date, how many shoppers said it worked or failed, and a link that opens the store with the offer. A code itself comes only where the brand has approved AI assistants; any other comes without it (code_on_page), linking to the store's vouchernaut.com page, where the shopper reveals it. The store can be named ("Arena Flowers"), or given by its slug or its vouchernaut.com page. Each link may earn Vouchernaut a commission, which every result discloses.

Input Schema

NameRequiredDescriptionDefault
kindNoOnly codes, only deals, or bothall
storeYesThe store's name, slug or vouchernaut.com store page URL

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds real context beyond that: result ordering matches the store page, gated code disclosure via `code_on_page` with a redirect to reveal, and affiliate-commission disclosure on links. It does not address behavior for an unresolvable store or any result-count limits.

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?

Front-loaded with what the tool returns, then mechanics, then input forms, then the commission caveat — a sensible order with no filler sentences. It is dense and slightly long, but each sentence carries information an agent needs.

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?

With no output schema, the description carries the return-value burden and does so well, listing savings, terms, end date, success/failure counts, and link. Only the failure/empty-result behavior for an unknown store is left unstated.

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%, so both parameters are already documented, including the `kind` enum. The description contributes only an example store name for `store` and never mentions the code/deal filter, so it adds little 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?

States a specific verb and resource ('every live discount code and deal Vouchernaut lists') and pins the scope to one UK store. The enumeration of returned fields makes it unmistakably different from sibling tools like search_stores or check_deal.

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 requirement of a known single store, plus the accepted identifier forms (name, slug, or vouchernaut.com page), gives a clear usage context: this is the per-store lookup, not a discovery search. It stops short of naming an alternative or stating when not to use it.

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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