How should Question Classifier: Front Desk Receptionist be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

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agentDifyUnverified

Question Classifier: Front Desk Receptionist

Digital receptionist that sorts and routes users inquiries to specialized AI agents based on their intent. 1. Install the OpenAI plugin from the Plugin Marketplace. 2. Authorize OpenAI in Dify by navigating to Tools → OpenAI → Authorize and entering your API key. 3. In the **Customer's Request** (Start) node, the user submits their inquiry. 4. Select an LLM in the **Question Classifier** node to automatically categorize the request as a Technical Support issue or a Billing issue. 5. Select an LLM in the **Technical Suppor

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Rank

Safety

Updated

Jun 1, 2026

Source

Dify

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. Last updated 6/1/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Difyvendor · observed May 30, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/dify-langgenius-question-classifier-front-desk-receptionist/snapshot"

Documentation

Dify

Install the OpenAI plugin from the Plugin Marketplace.
Authorize OpenAI in Dify by navigating to Tools → OpenAI → Authorize and entering your API key.
In the Customer's Request (Start) node, the user submits their inquiry.
Select an LLM in the Question Classifier node to automatically categorize the request as a Technical Support issue or a Billing issue.
Select an LLM in the Technical Support LLM node to draft a response for technical queries.
Select an LLM in the Billing Issue LLM node to draft a response for billing queries.
The Output node returns the appropriate department's response to the user.

Machine-readable data

The same record, as JSON, for agents and crawlers.

{
  "facts": [
    {
      "factKey": "vendor",
      "label": "Vendor",
      "value": "Dify",
      "category": "vendor",
      "href": "https://affiliate.dify.ai/06p00xtpqqwy-e8lw08?tid=362d6ff7-0295-452a-a501-4018b2f057b0",
      "sourceUrl": "https://affiliate.dify.ai/06p00xtpqqwy-e8lw08?tid=362d6ff7-0295-452a-a501-4018b2f057b0",
      "sourceType": "profile",
      "confidence": "medium",
      "observedAt": "2026-05-30T06:40:25.369Z",
      "isPublic": true,
      "metadata": {}
    },
    {
      "factKey": "handshake_status",
      "label": "Handshake status",
      "value": "UNKNOWN",
      "category": "security",
      "href": "https://www.xpersona.co/api/v1/agents/dify-langgenius-question-classifier-front-desk-receptionist/trust",
      "sourceUrl": "https://www.xpersona.co/api/v1/agents/dify-langgenius-question-classifier-front-desk-receptionist/trust",
      "sourceType": "trust",
      "confidence": "medium",
      "observedAt": null,
      "isPublic": true,
      "metadata": {}
    }
  ],
  "events": []
}

Record generated Oct 8, 2026.