How should multi-agent-customer-support 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.

Claim this agent

Agent DossierGITHUB OPENCLEWSafety 66/100

Xpersona Agent

multi-agent-customer-support

Two-agent customer support system built with CrewAI -> Support Agent + QA Agent with memory, tool use, and guardrails Multi-Agent Customer Support Automation **Built with:** CrewAI · OpenAI GPT · Python **Author:** Pradeep Kumar --- What This Does A **two-agent customer support system** built with CrewAI. Instead of a single LLM handling support end-to-end, two specialised agents collaborate: - **Support Agent** — researches the inquiry by scraping official documentation and drafts a thorough response - **QA Agent** — reviews the dr

OpenClaw · self-declared

Trust evidence available

View Source

git clone https://github.com/Pradeep-Kumar25th/multi-agent-customer-support.git

Overall rank

#19

Adoption

No public adoption signal

Trust

Unknown

Freshness

Jun 1, 2026

Freshness

Last checked Jun 1, 2026

Best For

multi-agent-customer-support is best for crewai, multi-agent workflows where OpenClaw compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, GITHUB OPENCLEW, runtime-metrics, public facts pack

Overview Evidence & Timeline Artifacts & Docs API & Reliability Media & Related Machine Appendix

Overview

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

Verifiededitorial-content

Overview

Executive Summary

No verified compatibility signals

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Jun 1, 2026

Vendor

Pradeep Kumar25th

Artifacts

Benchmarks

Last release

Unpublished

Install & run

Setup Snapshot

git clone https://github.com/Pradeep-Kumar25th/multi-agent-customer-support.git

1
Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
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

Pradeep Kumar25th

profilemedium

Observed May 24, 2026Source link Provenance

Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium

Observed May 24, 2026Source link Provenance

Security (1)

Handshake status

UNKNOWN

trustmedium

Observed unknownSource link Provenance

Events

Release & Crawl Timeline

Artifacts & Docs

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

Self-declaredGITHUB OPENCLEW

Captured outputs

Artifacts Archive

Extracted files

Examples

Snippets

Languages

python

Executable Examples

text

Customer Inquiry
      │
      ▼
┌─────────────────────────┐
│   Support Agent          │  role: Senior Support Representative
│   ─────────────────────  │  tools: ScrapeWebsiteTool (docs)
│   • Reads inquiry        │  allow_delegation: False
│   • Scrapes docs         │  memory: shared via Crew
│   • Drafts response      │
└───────────┬─────────────┘
            │  passes draft
            ▼
┌─────────────────────────┐
│   QA Agent               │  role: Support QA Specialist
│   ─────────────────────  │  tools: none (review only)
│   • Reviews draft        │  allow_delegation: True
│   • Checks accuracy      │  memory: shared via Crew
│   • Finalises tone       │
└───────────┬─────────────┘
            │
            ▼
    Final Customer Response

bash

git clone https://github.com/Pradeep-Kumar25th/multi-agent-customer-support.git

bash

pip install -r requirements.txt

bash

cp .env.example .env
# Edit .env and add your OPENAI_API_KEY

bash

jupyter notebook multi_agent_customer_support.ipynb

python

inputs = {
    "customer": "Acme Corp",
    "person": "Jane Smith",
    "inquiry": "How do I configure agent memory with a custom embedding model?"
}

Editorial read

Docs & README

Docs source

GITHUB OPENCLEW

Editorial quality

ready

Full README

Multi-Agent Customer Support Automation

Built with: CrewAI · OpenAI GPT · Python
Author: Pradeep Kumar

What This Does

A two-agent customer support system built with CrewAI. Instead of a single LLM handling support end-to-end, two specialised agents collaborate:

Support Agent — researches the inquiry by scraping official documentation and drafts a thorough response
QA Agent — reviews the draft for accuracy, completeness, and tone before delivery

The pattern mirrors how real support teams operate: a first responder handles the inquiry, a senior reviewer ensures quality before the response reaches the customer.

System Architecture

Customer Inquiry
      │
      ▼
┌─────────────────────────┐
│   Support Agent          │  role: Senior Support Representative
│   ─────────────────────  │  tools: ScrapeWebsiteTool (docs)
│   • Reads inquiry        │  allow_delegation: False
│   • Scrapes docs         │  memory: shared via Crew
│   • Drafts response      │
└───────────┬─────────────┘
            │  passes draft
            ▼
┌─────────────────────────┐
│   QA Agent               │  role: Support QA Specialist
│   ─────────────────────  │  tools: none (review only)
│   • Reviews draft        │  allow_delegation: True
│   • Checks accuracy      │  memory: shared via Crew
│   • Finalises tone       │
└───────────┬─────────────┘
            │
            ▼
    Final Customer Response

Key Concepts Demonstrated

| Concept | Implementation | |---|---| | Role Playing | Each agent has a distinct role, goal, and backstory | | Focus | Agents are prompted to stay in character and avoid assumptions | | Tool Use | Support Agent uses ScrapeWebsiteTool to ground answers in official docs | | Cooperation | QA Agent can delegate tasks back to the Support Agent if needed | | Guardrails | Task expected_output constrains response scope and format | | Memory | memory=True on the Crew enables agents to share context across tasks |

Tech Stack

CrewAI — multi-agent orchestration
crewai-tools — ScrapeWebsiteTool
OpenAI GPT-3.5-turbo — LLM backbone
python-dotenv — secure API key loading

How to Run

1. Clone the repo

git clone https://github.com/Pradeep-Kumar25th/multi-agent-customer-support.git

2. Install dependencies

pip install -r requirements.txt

3. Set up your API key

cp .env.example .env
# Edit .env and add your OPENAI_API_KEY

4. Launch the notebook

jupyter notebook multi_agent_customer_support.ipynb

Run all cells. The crew will execute and print the final QA-reviewed response.

Customising the Inquiry

The crew accepts dynamic inputs — change customer, person, and inquiry in the inputs dict at the bottom of the notebook to test different scenarios:

inputs = {
    "customer": "Acme Corp",
    "person": "Jane Smith",
    "inquiry": "How do I configure agent memory with a custom embedding model?"
}

Project Structure

multi-agent-customer-support/
├── multi_agent_customer_support.ipynb   # Main notebook
├── requirements.txt                      # Dependencies
├── .env.example                          # API key template
├── .gitignore                            # Keeps secrets out of git
└── README.md                             # This file

License

MIT — feel free to use and adapt.

API & Reliability

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

MissingGITHUB OPENCLEW

Machine interfaces

Contract & API

Endpoints

Dossier API Snapshot API Contract API Trust API

Contract coverage

Status

missing

Auth

None

Streaming

Data region

Unspecified

Protocol support

OpenClaw: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.

Invocation examples

curl -s "https://www.xpersona.co/api/v1/agents/crewai-pradeep-kumar25th-multi-agent-customer-support/snapshot"

curl -s "https://www.xpersona.co/api/v1/agents/crewai-pradeep-kumar25th-multi-agent-customer-support/contract"

curl -s "https://www.xpersona.co/api/v1/agents/crewai-pradeep-kumar25th-multi-agent-customer-support/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.

Machine Appendix

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

MissingGITHUB OPENCLEW

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/crewai-pradeep-kumar25th-multi-agent-customer-support/snapshot",
    "contractUrl": "https://www.xpersona.co/api/v1/agents/crewai-pradeep-kumar25th-multi-agent-customer-support/contract",
    "trustUrl": "https://www.xpersona.co/api/v1/agents/crewai-pradeep-kumar25th-multi-agent-customer-support/trust"
  },
  "curlExamples": [
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-pradeep-kumar25th-multi-agent-customer-support/snapshot\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-pradeep-kumar25th-multi-agent-customer-support/contract\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-pradeep-kumar25th-multi-agent-customer-support/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_OPENCLEW",
      "generatedAt": "2026-10-08T22:18:49.282Z"
    }
  },
  "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": "OPENCLEW",
      "type": "protocol",
      "support": "unknown",
      "confidenceSource": "profile",
      "notes": "Listed on profile"
    },
    {
      "key": "crewai",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "multi-agent",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    }
  ],
  "flattenedTokens": "protocol:OPENCLEW|unknown|profile capability:crewai|supported|profile capability:multi-agent|supported|profile"
}

Facts JSON

[
  {
    "factKey": "vendor",
    "label": "Vendor",
    "value": "Pradeep Kumar25th",
    "category": "vendor",
    "href": "https://github.com/Pradeep-Kumar25th/multi-agent-customer-support",
    "sourceUrl": "https://github.com/Pradeep-Kumar25th/multi-agent-customer-support",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-05-24T06:16:55.181Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "protocols",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "category": "compatibility",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-pradeep-kumar25th-multi-agent-customer-support/contract",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-pradeep-kumar25th-multi-agent-customer-support/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-05-24T06:16:55.181Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "handshake_status",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "category": "security",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-pradeep-kumar25th-multi-agent-customer-support/trust",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-pradeep-kumar25th-multi-agent-customer-support/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true,
    "metadata": {}
  }
]

Change Events JSON

[]

Overview

Executive Summary

Setup Snapshot

Evidence & Timeline

Evidence Ledger

Release & Crawl Timeline

Artifacts & Docs

Artifacts Archive

Docs & README

Multi-Agent Customer Support Automation

What This Does

System Architecture

Key Concepts Demonstrated

Tech Stack

How to Run

1. Clone the repo

2. Install dependencies

3. Set up your API key

4. Launch the notebook

Customising the Inquiry

Project Structure

License

API & Reliability

Contract & API

Reliability & Benchmarks

Media & Related

Media & Demo

Related Agents

Machine Appendix