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48x-ai

@marketbasketanalysis/mcp

by 48x-ai

get_opportunities

Discover ranked bundle and cross-sell opportunities mined from order history. Get support, confidence, lift, and revenue-weighted scores to prioritize which product bundles to publish or act on.

Instructions

List the merchant's ranked bundle / cross-sell opportunities mined from order history, with support / confidence / lift / revenue-weighted score. Use this when a merchant asks 'what are my top opportunities?', 'show me the best bundles I haven't published yet', or 'what should I prioritize?'. Pair with triage_opportunity to act on a specific one. Merchant-ops surface: BigCommerce today; on other platforms merchants manage this from the admin, and the tool returns a clear not-available message.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax opportunities to return. Default 10, max 50.
statusNoFilter by opportunity status. Defaults to 'proposed' (untriaged).proposed

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.7.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses platform-dependent behavior (BigCommerce today, clear not-available message elsewhere) and implies a read-only listing operation. It could add response-shape details, but the disclosed behavior goes beyond the bare minimum.

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?

Four compact sentences, front-loaded with the primary purpose and followed by usage examples, a pairing note, and platform behavior. Every sentence earns its place 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?

Given only two optional parameters and no output schema, the description is sufficient for correct invocation: it defines what is returned (ranked opportunities with scores), the default status context, and the cross-platform fallback. A mention of the response fields would make it fully complete.

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 both parameters already documented clearly, including defaults and enum options. The description does not add parameter-specific meaning beyond the schema, so the baseline 3 is appropriate.

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 clearly states a specific verb (list), resource (merchant's ranked bundle/cross-sell opportunities), and scoring fields (support/confidence/lift/revenue-weighted score). It does not explicitly contrast itself with sibling tools like get_recommendations or find_substitutes, so it stops short of a 5.

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 description gives concrete example user queries ('what are my top opportunities?', 'show me the best bundles I haven't published yet') and appropriately pairs with triage_opportunity for acting on a result. It provides clear context for when to use the tool, though it does not state when not to use it or name alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.