SiteCheck Shop & Social

Falabella Chile product search: product ID, name, brand

ecommerce_falabella_latam

Read-only

Falabella Chile product search: product ID, name, brand, seller, prices in CLP (Falabella CMR card price, internet/event price and crossed-out normal price) with discount badge, rating and review count, best-seller and sponsored flags, delivery stickers (e.g. arrives tomorrow), image and product URL; 48+ per page plus the total number of results. Price: $0.002 in USDC per successful call, paid with x402 (Base, Solana or Arc); failed calls are not charged.

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": {
      "q": "<q>"
    },
    "name": "ecommerce_falabella_latam"
  }
}

Input Schema

Name	Required	Description	Default
`q`	Yes	Search words in Spanish or English, e.g. notebook, refrigerador (required)
`page`	No	Page number 1 to 50 (default 1)

Output Schema

Name	Required	Description	Default
`q`	No
`page`	No
`count`	No
`total`	No
`source`	No
`country`	No
`currency`	No
`products`	No
`checkedAt`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 23, 2026

TDQS

A3.6/5.0

Behavior4/5

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

Annotations already establish readOnly and openWorld, so the safety profile is covered; the description then adds genuinely non-obvious context: 48+ results per page plus a total count, and a pay-per-call model ($0.002 USDC via x402 on Base/Solana/Arc) where failed calls are free. The billing and failure-charging disclosure is exactly the kind of behavioral detail the schema cannot express. It stops short of noting rate limits, caching, or latency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded, which is good, but the body is a dense semicolon-delimited dump of return fields that duplicates what the output schema already exposes. The pricing sentence is well-placed and earns its space; the field enumeration largely does not.

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 two-parameter search tool with an output schema, this covers the essentials an agent needs before calling: scope, result density, paging, and cost. The redundant field listing is wasted effort rather than a gap, and nothing critical — such as failure modes or empty-result behavior — is glaringly absent.

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 'q' documented with Spanish/English examples and 'page' bounded 1–50, so the schema carries the load. The description adds only marginal meaning by noting result volume per page, which helps an agent reason about the page parameter. 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?

States a specific verb and resource — product search on Falabella Chile — and enumerates what the results contain (prices in CLP, ratings, seller, delivery stickers). Among ~50 retailer siblings, the named retailer is what separates it. Minor friction: the tool name says 'latam' while the description scopes it to Chile, leaving a small ambiguity an agent must resolve by inference.

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 only implied: an agent infers it should call this when it wants Falabella Chile catalog or pricing data. There is no explicit statement of when to prefer it over a sibling retailer tool, no coverage/assortment scope, and no note on what to do if results are empty. Adequate but leaves routing to inference.

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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