Xpersona
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Xpersona Agent

Random Question Generation

This Chatflow template generates a custom number of practice questions on a user-specified subject. Users type a natural-language request (e.g. "Give me 3 Linear Algebra questions from Chapter 3") into the chat. A Knowledge Retrieval node fetches matching items from a connected question-bank knowledge base, and an LLM node filters and formats them according to the requested subject and count. The selected questions are streamed back as the assistant's reply. Ideal for teachers and learners who need quick, on-demand exercises without writing them by hand. 1. **Create a new Chatflow.** In Dify Studio, click *Create Application* → *Chatflow*. Name it Random_question_generation. 2. **Add a USER INPUT node.** This is the entry point where the user's request (e.g. *"Give me 3 Linear Algebra questions"*) enters the workflow. 3. **Add a KNOWLEDGE RETRIEVAL node** and connect it to a knowledge base that contains your question–answer pairs. A Markdown-formatted Excel question

Trust evidence available
View on Dify

Overall rank

#90

Adoption

No public adoption signal

Trust

Unknown

Freshness

Oct 9, 2026

Freshness

Last checked Oct 9, 2026

Best For

Random Question Generation is best for workflow, others, openai workflows where documented compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, Dify, runtime-metrics, public facts pack

OverviewEvidence & TimelineArtifacts & DocsAPI & ReliabilityMedia & RelatedMachine Appendix

Overview

Key links, install path, reliability highlights, and the shortest practical read before diving into the crawl record.

Verifiededitorial-content

Overview

Executive Summary

This Chatflow template generates a custom number of practice questions on a user-specified subject. Users type a natural-language request (e.g. "Give me 3 Linear Algebra questions from Chapter 3") into the chat. A Knowledge Retrieval node fetches matching items from a connected question-bank knowledge base, and an LLM node filters and formats them according to the requested subject and count. The selected questions are streamed back as the assistant's reply. Ideal for teachers and learners who need quick, on-demand exercises without writing them by hand. 1. **Create a new Chatflow.** In Dify Studio, click *Create Application* → *Chatflow*. Name it Random_question_generation. 2. **Add a USER INPUT node.** This is the entry point where the user's request (e.g. *"Give me 3 Linear Algebra questions"*) enters the workflow. 3. **Add a KNOWLEDGE RETRIEVAL node** and connect it to a knowledge base that contains your question–answer pairs. A Markdown-formatted Excel question Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.

No verified compatibility signals

Trust score

Unknown

Compatibility

Profile only

Freshness

Oct 9, 2026

Vendor

Dify

Artifacts

0

Benchmarks

0

Last release

Unpublished

Install & run

Setup Snapshot

  1. 1

    Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.

  2. 2

    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.

Evidence & Timeline

Public facts grouped by evidence type, plus release and crawl events with provenance and freshness.

Verifiededitorial-content

Public facts

Evidence Ledger

Vendor (1)

Vendor

Dify

profilemedium
Observed Oct 9, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance

Events

Release & Crawl Timeline

Artifacts & Docs

Parameters, dependencies, examples, extracted files, editorial overview, and the complete README when available.

Self-declaredDify

Captured outputs

Artifacts Archive

Extracted files

0

Examples

0

Snippets

0

Languages

en

Editorial read

Docs & README

Docs source

Dify

Editorial quality

ready

This Chatflow template generates a custom number of practice questions on a user-specified subject. Users type a natural-language request (e.g. "Give me 3 Linear Algebra questions from Chapter 3") into the chat. A Knowledge Retrieval node fetches matching items from a connected question-bank knowledge base, and an LLM node filters and formats them according to the requested subject and count. The selected questions are streamed back as the assistant's reply. Ideal for teachers and learners who need quick, on-demand exercises without writing them by hand. 1. **Create a new Chatflow.** In Dify Studio, click *Create Application* → *Chatflow*. Name it Random_question_generation. 2. **Add a USER INPUT node.** This is the entry point where the user's request (e.g. *"Give me 3 Linear Algebra questions"*) enters the workflow. 3. **Add a KNOWLEDGE RETRIEVAL node** and connect it to a knowledge base that contains your question–answer pairs. A Markdown-formatted Excel question

Full README

  1. Create a new Chatflow. In Dify Studio, click Create Application → Chatflow. Name it Random_question_generation.

  2. Add a USER INPUT node. This is the entry point where the user's request (e.g. "Give me 3 Linear Algebra questions") enters the workflow.

  3. Add a KNOWLEDGE RETRIEVAL node and connect it to a knowledge base that contains your question–answer pairs. A Markdown-formatted Excel question bank is recommended.

  4. Add an LLM node. Pick a chat-capable model such as GPT-5 or GPT-4o-mini.

  5. Paste the prompt into the LLM node's SYSTEM field. The prompt defines an exercise-filter-and-output agent and references two variables:

    • {{#sys.query#}} — the user's natural-language request
    • {{#context#}} — items returned by the Knowledge Retrieval node

    The prompt lists six rules: parse intent · filter by subject · answer-switch · quantity-adapt · output format · stay on-topic.

  6. Add an ANSWER node and connect the LLM output to it so the assistant can stream the questions back to the user.

  7. Save and Test Run. Send a sample request such as "Give me 3 Linear Algebra questions" and verify the reply contains exactly the requested number of matching questions.

API & Reliability

Machine endpoints, contract coverage, trust signals, runtime metrics, benchmarks, and guardrails for agent-to-agent use.

MissingDify

Machine interfaces

Contract & API

Endpoints

Dossier APISnapshot APIContract APITrust API

Contract coverage

Status

missing

Auth

None

Streaming

No

Data region

Unspecified

Protocol support

No protocol metadata captured.

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.
Invocation examples
curl -s "https://www.xpersona.co/api/v1/agents/dify-toby-random-question-generation/snapshot"
curl -s "https://www.xpersona.co/api/v1/agents/dify-toby-random-question-generation/contract"
curl -s "https://www.xpersona.co/api/v1/agents/dify-toby-random-question-generation/trust"

Operational fit

Reliability & Benchmarks

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.
No benchmark suites or observed failure patterns are available.

Media & Related

Public screenshots, demo and owner links, plus neighboring agents from the same ecosystem for shortlist building.

Missingno-media

Visual context

Media & Demo

No screenshots, media assets, or demo links are available.

Comparison set

Related Agents

No close protocol neighbors were found.
Agent hubMore from this source

Machine Appendix

Raw contract, invocation, trust, capability, facts, and change-event payloads for machine-side inspection.

MissingDify

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://www.xpersona.co/api/v1/agents/dify-toby-random-question-generation/snapshot",
    "contractUrl": "https://www.xpersona.co/api/v1/agents/dify-toby-random-question-generation/contract",
    "trustUrl": "https://www.xpersona.co/api/v1/agents/dify-toby-random-question-generation/trust"
  },
  "curlExamples": [
    "curl -s \"https://www.xpersona.co/api/v1/agents/dify-toby-random-question-generation/snapshot\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/dify-toby-random-question-generation/contract\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/dify-toby-random-question-generation/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": []
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "DIFY_MARKETPLACE",
      "generatedAt": "2026-10-09T03:18:21.434Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "workflow",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "others",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "openai",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    }
  ],
  "flattenedTokens": "capability:workflow|supported|profile capability:others|supported|profile capability:openai|supported|profile"
}

Facts JSON

[
  {
    "factKey": "vendor",
    "category": "vendor",
    "label": "Vendor",
    "value": "Dify",
    "href": "https://marketplace.dify.ai/api/v1/templates/1c47faa0-2d32-45a3-b054-97ea362334c9",
    "sourceUrl": "https://marketplace.dify.ai/api/v1/templates/1c47faa0-2d32-45a3-b054-97ea362334c9",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-10-09T01:20:55.238Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://www.xpersona.co/api/v1/agents/dify-toby-random-question-generation/trust",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/dify-toby-random-question-generation/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[]

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