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Feedico: coupons, deals & products

Search coupons

search_coupons
Read-only

Find active coupon codes and deals, by store name and/or keyword. Use for questions like "is there a discount code for Nike?" Returns code, title, end date, store and a tracked link.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many results (default 8)
queryNoKeyword in the offer, e.g. "free shipping", "20%"
storeNoStore name or domain, e.g. "nike", "adidas.com"
countriesNoISO country codes to limit offers to, e.g. ["US"] or ["GB","IE"]
endingWithinDaysNoOnly offers that end within N days

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds real behavioral value by disclosing the return contents (code, title, end date, store) and noting that the link is tracked, which matters for an open-world search with no output schema. It still says nothing about result ranking or empty-result behavior.

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, both front-loaded: the core capability first, then a routing example. Every clause carries information — what it finds, how to filter it, and what it returns — with 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?

With no output schema, the description usefully summarizes the returned fields, and the annotations cover safety and open-world reach. It is nearly complete for a 5-parameter search, though limit/pagination behavior and how results are ordered are left to the 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 description coverage is 100%, so all five parameters (limit, query, store, countries, endingWithinDays) are already documented with examples and bounds. The description restates store/keyword filtering but adds no syntax, format, or combination semantics beyond the schema, so the baseline 3 applies.

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?

The description states a specific verb and resource ('Find active coupon codes and deals') and names the two filter dimensions (store name and/or keyword), so the agent knows exactly what this tool retrieves. It does not explicitly contrast itself with siblings like search_products or search_stores, but the coupon-specific resource makes it distinguishable in practice.

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?

It gives concrete usage context with a worked example ('is there a discount code for Nike?'), which clearly signals when to reach for this tool. It stops short of naming alternatives or exclusions, so the agent must infer that product/store lookups belong to the 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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