Papyras Coupons

Top offers in a category

top_offers_in_category

Read-onlyIdempotent

The strongest live offers in a shopping category, one per store (e.g. "fashion", "electronics", "travel", "running shoes", "vpn", "pet food"). Category can be a name or slug.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "category": "<category>"
    },
    "name": "top_offers_in_category"
  }
}

Input Schema

Name	Required	Description
`limit`	No	How many offers to return (default 10, max 30).
`country`	No	Optional ISO country code (US, UK, DE, …) to prefer stores that serve that country. Worldwide stores are always included.
`category`	Yes	Category name or slug.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 12, 2026

TDQS

A3.7/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world read behavior, so the baseline is low. The description still adds real semantics beyond them: results are ranked ('strongest') and deduplicated to one per store, and offers are 'live'. It omits how 'strongest' is computed and whether results are stale-cached.

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?

A single front-loaded sentence with the key scoping rule first and value examples trailing. The list of six category examples is slightly longer than needed to convey the idea, but each is short and the whole definition carries no filler.

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 simple read-only retrieval tool with three fully documented parameters and no output schema, the description covers the essentials: what is returned (offers), how they are scoped (one per store), and what 'live' and 'strongest' imply. The remaining gap is that offer shape and ranking basis are left unspecified, which matters somewhat with 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 all three parameters documented including country preference and worldwide fallback. The description's only parameter-relevant sentence ('category can be a name or slug') duplicates the schema text verbatim, adding no new meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific resource (offers in a shopping category) and a distinguishing constraint: 'strongest live offers, one per store.' The deduplication rule separates it conceptually from a per-store listing, but it never names the sibling it differs from (e.g. get_store_offers), so the agent must infer the boundary.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

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

Usage is implied rather than stated: examples of category values ("fashion", "vpn", "pet food") show the expected granularity, and 'category can be a name or slug' clarifies input form. There is no explicit when-to-use/when-not guidance and no routing to alternatives such as get_store_offers or best_offer_for_url.

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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