How should multi-agent-customer-support be evaluated before use?

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

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.

Crawler Summary

multi-agent-customer-support answer-first brief

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 Capability contract not published. No trust telemetry is available yet. Last updated 4/15/2026.

Freshness

Last checked 4/15/2026

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 REPOS, runtime-metrics, public facts pack

Card Facts Snapshot Contract Trust

Claim this agent

Agent DossierGITHUB REPOSSafety: 66/100

multi-agent-customer-support

OpenClawself-declared

Public facts

Change events

Artifacts

Freshness

Apr 15, 2026

Verifiededitorial-contentNo verified compatibility signals

Capability contract not published. No trust telemetry is available yet. Last updated 4/15/2026.

Trust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Apr 15, 2026

Vendor

Pradeep Kumar25th

Artifacts

Benchmarks

Last release

Unpublished

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

Summary

Capability contract not published. No trust telemetry is available yet. Last updated 4/15/2026.

View Source

Setup snapshot

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 Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content

Vendor (1)

Vendor

Pradeep Kumar25th

profilemedium

Observed Apr 15, 2026Source link Provenance

Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium

Observed Apr 15, 2026Source link Provenance

Security (1)

Handshake status

UNKNOWN

trustmedium

Observed unknownSource link Provenance

Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium

Observed Apr 15, 2026Source link Provenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Docs Update

Docs refreshed: Sign in to GitHub · GitHub

search_documentmedium

Fresh crawlable documentation was indexed for the official domain.

Observed Apr 15, 2026

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB REPOS

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?"
}

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB REPOS

Docs source

GITHUB REPOS

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.

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

MissingGITHUB REPOS

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

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

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

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

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 & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media

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

Related Agents

Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

Self-declaredprotocol-neighbors

GITHUB_REPOSactivepieces

Rank

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

Traction

No public download signal

Freshness

Updated 2d ago

OPENCLAW

GITHUB_REPOScherry-studio

Rank

AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs

Traction

No public download signal

Freshness

Updated 5d ago

MCPOPENCLAW

GITHUB_REPOSAionUi

Rank

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

Traction

No public download signal

Freshness

Updated 6d ago

MCPOPENCLAW

GITHUB_REPOSCopilotKit

Rank

The Frontend for Agents & Generative UI. React + Angular

Traction

No public download signal

Freshness

Updated 23d ago

OPENCLAW

Machine Appendix

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://xpersona.co/api/v1/agents/crewai-pradeep-kumar25th-multi-agent-customer-support/snapshot",
    "contractUrl": "https://xpersona.co/api/v1/agents/crewai-pradeep-kumar25th-multi-agent-customer-support/contract",
    "trustUrl": "https://xpersona.co/api/v1/agents/crewai-pradeep-kumar25th-multi-agent-customer-support/trust"
  },
  "curlExamples": [
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-pradeep-kumar25th-multi-agent-customer-support/snapshot\"",
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-pradeep-kumar25th-multi-agent-customer-support/contract\"",
    "curl -s \"https://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_REPOS",
      "generatedAt": "2026-04-16T23:39:19.545Z"
    }
  },
  "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",
    "category": "vendor",
    "label": "Vendor",
    "value": "Pradeep Kumar25th",
    "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": "2026-04-15T06:04:38.337Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://xpersona.co/api/v1/agents/crewai-pradeep-kumar25th-multi-agent-customer-support/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/crewai-pradeep-kumar25th-multi-agent-customer-support/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-04-15T06:04:38.337Z",
    "isPublic": true
  },
  {
    "factKey": "docs_crawl",
    "category": "integration",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://xpersona.co/api/v1/agents/crewai-pradeep-kumar25th-multi-agent-customer-support/trust",
    "sourceUrl": "https://xpersona.co/api/v1/agents/crewai-pradeep-kumar25th-multi-agent-customer-support/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub · GitHub",
    "description": "Fresh crawlable documentation was indexed for the official domain.",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  }
]