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What is discounted right now

get_deals

For a "find something on offer" task. GET /api/agent/browse/deals?tab=, where tab is markdowns, refurbished, top-rated, brands, or door: for one department. No wallet and no signature. Every item carries cachedAt, which is when that price was true: pass it as a candidate's priceAt to compare_landed_cost. A selection over rows this site has already cached, so it costs no catalogue call. An unknown tab is refused with 400 rather than guessed at. A sticker discount is not a cheaper order: rank with compare_landed_cost before you quote.

Input Schema

NameRequiredDescriptionDefault
tabYesmarkdowns, refurbished, top-rated, brands, or door:<slug> with a slug from list_categories.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

With zero annotations the description carries the full burden and does so: no wallet or signature required, results come from cached rows so no catalogue call is spent, an unknown tab returns 400 rather than being guessed at, and each row exposes cachedAt as the timestamp of price validity. That covers auth, cost, error behavior, and freshness — well beyond the schema.

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 the task framing and the endpoint, and nearly every sentence adds a distinct operational fact (auth, caching, 400 on bad tab, cachedAt handoff). The telegraphic phrasing ('A selection over rows this site has already cached') is slightly compressed and costs a beat of readability.

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?

For a one-parameter, non-destructive read with no output schema and no annotations, the description covers invocation, auth, cost, failure mode, and the key returned field. It does not describe the shape of the returned deal rows beyond cachedAt, which leaves the agent guessing about other fields.

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

Parameters4/5

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

Schema coverage is 100%, so the single tab parameter is already documented, but the description adds meaning by explaining that door:<slug> scopes to one department and by tying the slug source to list_categories. It still does not spell out expected slug format or what each named tab actually contains.

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 ('GET /api/agent/browse/deals?tab=<tab>') and frames the task it serves ('find something on offer'). The enumeration of tabs plus the note that results come from already-cached rows distinguishes it from catalogue-searching siblings like search_products and get_prices.

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?

Gives a clear trigger ('For a "find something on offer" task') and routes the agent elsewhere for the adjacent step: rank with compare_landed_cost before quoting, and pull the door slug from list_categories. It stops short of stating when this tool should NOT be used (e.g. live pricing versus cached rows), so no explicit exclusion is offered.

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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