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marketbasketanalysis-mcp

by io.github.48x-ai

explain_drift

Explain ONE drift alert: return its prior and current confidence (plus support, lift, and order sample count when the rule is still live) and a short plain-language narrative of how the pair moved versus the prior mining run. Use this when a merchant asks 'why did this pair drift?', 'explain this alert', or 'what changed for these two products?' after seeing it in get_drift_alerts. Different from get_drift_alerts: that lists the feed, this drills into a single alert_id with the change spelled out in a sentence. Handles a disappeared pair gracefully (only the prior confidence is available). BigCommerce only today.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
alert_idYesThe id of the drift alert to explain, from get_drift_alerts.

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals conditional return content (support, lift, and order sample count only when the rule is still live), graceful handling of disappeared pairs, and the BigCommerce-only platform limitation. It does not explicitly state read-only/idempotent behavior, but the return-oriented wording makes the tool's non-mutating intent clear.

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?

The description is appropriately sized at three sentences and front-loads the core purpose before covering usage context, sibling distinction, and edge-case behavior. Every sentence contributes non-redundant value, including the platform limitation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given a single required parameter and no output schema, the description gives an agent everything needed to call the tool correctly: what to pass, what will be returned, when to use it, which sibling it differs from, and how a missing pair is handled. No critical operational detail appears to be missing.

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%, and the alert_id parameter is already documented as coming from get_drift_alerts. The description reinforces this source and uses alert_id contextually, but it adds no new format, type, or validation details beyond what the input schema already provides.

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?

The description states a specific verb and resource: 'Explain ONE drift alert' and enumerates what it returns. It also explicitly differentiates itself from get_drift_alerts by noting that the sibling lists the feed while this tool drills into a single alert_id.

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

Usage Guidelines5/5

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

The description provides clear triggering scenarios with exact merchant phrasings like 'why did this pair drift?' and says to use it after seeing an alert in get_drift_alerts. It also names the alternative get_drift_alerts and explains the difference, which helps an agent select the correct sibling.

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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TDQS

A4.1/5.0
Disambiguation4/5

Tools map largely one-to-one to distinct actions, and descriptions explicitly differentiate similar-looking pairs like get_recommendations vs. get_bundle_for_cart vs. find_substitutes. However, score_cross_sell vs. analyze_basket and get_rationale vs. explain_opportunity could still confuse an agent, since both score/explain overlapping concepts. Overall ambiguity is low but not zero.

Naming Consistency5/5

All tool names follow a consistent snake_case verb_noun pattern: get_* for retrieval, explain_* for drill-downs, score_* for validations, and action verbs for state changes. No camelCase or mixed conventions are present, making the naming highly predictable.

Tool Count3/5

19 tools is on the heavy side for a single server and exceeds the typical 3–15 range, even though most tools have distinct purposes. The large count reflects a broad feature set covering recommendations, alerts, forecasting, reorder, returns, and weekly planning, but a few tools could be consolidated. It feels slightly bloated rather than egregiously so.

Completeness4/5

The surface covers the main discovery–evaluation–action workflow: recommend, score, explain, triage, plan, and forecast. Minor gaps exist—there is no direct tool for creating or editing a bundle outside of weekly-plan actions, and no catalog-browsing capability—but those are largely external concerns. The workflow is coherent with no major dead ends.

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