Github ReposUpdated 3h agoRank 70
AionUi
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!
MCPOPENCLAW
Crawler Summary
crewai-customer-support-app answer-first brief
Customer Support System made of three agents that run one after another (sequentially) using the CrewAI framework, with a Streamlit user interface. streamlit run app.py Testing sequence Query 1: What responsibility does an Amazon.in customer have for maintaining the confidentiality of their account and password? Query 2: How does Amazon.in use the personal information it collects? Query 3: What is Amazon.in's employee vacation policy? RAG test queries Privacy Notice What types of personal information does Amazon.in collect from customers? How does Amazon.in use Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.
Freshness
Last checked 10/9/2026
Best For
crewai-customer-support-app 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
Agent DossierGITHUB REPOSSafety: 66/100
crewai-customer-support-app
Customer Support System made of three agents that run one after another (sequentially) using the CrewAI framework, with a Streamlit user interface. streamlit run app.py Testing sequence Query 1: What responsibility does an Amazon.in customer have for maintaining the confidentiality of their account and password? Query 2: How does Amazon.in use the personal information it collects? Query 3: What is Amazon.in's employee vacation policy? RAG test queries Privacy Notice What types of personal information does Amazon.in collect from customers? How does Amazon.in use
OpenClawself-declared
Public facts
4
Change events
1
Artifacts
0
Freshness
Oct 9, 2026
Verifiededitorial-contentNo verified compatibility signals
Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.
Trust evidence available
Trust score
Unknown
Compatibility
OpenClaw
Freshness
Oct 9, 2026
Vendor
Vebalakrishnan
Artifacts
0
Benchmarks
0
Last release
Unpublished
Executive Summary
Key links, install path, and a quick operational read before the deeper crawl record.
Summary
Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.
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.
Vendor (1)
Vendor
Vebalakrishnan
profilemedium
Compatibility (1)
Protocol compatibility
OpenClaw
contractmedium
Security (1)
Handshake status
UNKNOWN
trustmedium
Integration (1)
Crawlable docs
6 indexed pages on the official domain
search_documentmedium
Release & Crawl Timeline
Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.
Artifacts Archive
Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.
Extracted files
0
Examples
0
Snippets
0
Languages
python
Docs & README
Full documentation captured from public sources, including the complete README when available.
Docs source
GITHUB REPOS
Editorial quality
ready
Customer Support System made of three agents that run one after another (sequentially) using the CrewAI framework, with a Streamlit user interface. streamlit run app.py Testing sequence Query 1: What responsibility does an Amazon.in customer have for maintaining the confidentiality of their account and password? Query 2: How does Amazon.in use the personal information it collects? Query 3: What is Amazon.in's employee vacation policy? RAG test queries Privacy Notice What types of personal information does Amazon.in collect from customers? How does Amazon.in use
Full README
streamlit run app.py
Testing sequence
Query 1: What responsibility does an Amazon.in customer have for maintaining the confidentiality of their account and password?
Query 2: How does Amazon.in use the personal information it collects?
Query 3: What is Amazon.in's employee vacation policy?
RAG test queries
Privacy Notice
What types of personal information does Amazon.in collect from customers?
How does Amazon.in use the personal information it collects?
What information does Amazon automatically collect when customers use its services?
Does Amazon.in receive information about customers from other sources?
What are the purposes for which Amazon uses customer information?
Conditions of Use
What are the customer's responsibilities when using an Amazon.in account?
What does Amazon.in say about unauthorized access to an account?
What restrictions does Amazon.in place on using its website?
What does Amazon.in say about electronic communications?
What are the conditions for using Amazon.in services?
Project Architecture
┌─────────────────────┐
│ PDF Files │
│ input_pdfs/ │
└──────────┬──────────┘
│
▼
┌─────────────────────┐
│ PDF Text Loader │
│ PyPDFLoader │
└──────────┬──────────┘
│
▼
┌─────────────────────┐
│ Text Splitter │
│ RecursiveCharacter │
│ TextSplitter │
└──────────┬──────────┘
│
▼
┌─────────────────────┐
│ Embeddings │
│ HuggingFace MiniLM │
└──────────┬──────────┘
│
▼
┌───────────────────────────┐
│ LOCAL FAISS DB │
│ faiss_db/ │
└─────────────┬─────────────┘
│
│ Assistant RAG Tool
▼
User Query ───────► ┌─────────────────────┐ │ 1. Assistant │ │ FAISS RAG ONLY │ └──────────┬──────────┘ │ ▼ ┌─────────────────────┐ │ 2. Web Search │ │ Search Internet │ └──────────┬──────────┘ │ ▼ ┌─────────────────────┐ │ 3. Entry Agent │ │ Append to ONE file │ └──────────┬──────────┘ │ ┌─────────────┴─────────────┐ ▼ ▼ Streamlit Answer 1 Streamlit Answer 2
Project structure
customer_support/ │ ├── app.py ├── .env ├── .gitignore │ ├── input_pdfs/ │ ├── Amazon.in Privacy Notice - Amazon Customer Service.pdf │ └── Conditions of Use - Amazon Customer Service.pdf │ ├── faiss_db/ │ ├── index.faiss │ └── index.pkl │ └── support_entries/ └── customer_support_entries.txt
What happens the first time you run it?
When you submit the first question: PDF ↓ PyPDFLoader ↓ Text chunks ↓ all-MiniLM-L6-v2 ↓ FAISS ↓ faiss_db/
You will get:
faiss_db/ ├── index.faiss └── index.pkl
Agent config
Assistant │ └── FAISS → local PDF knowledge
Web Search Assistant │ └── Serper → Internet
Entry Agent │ └── customer_support_entries.txt
Final Design
┌───────────────┐
│ Local PDFs │
└───────┬───────┘
│
▼
┌───────────────┐
│ FAISS │
│ Persistent │
└───────┬───────┘
│
RAG ONLY
│
▼
┌───────────────┐
│ Agent 1 │
│ Assistant │
└───────┬───────┘
│
▼
┌───────────────┐
│ Agent 2 │
│ Web Search │
└───────┬───────┘
│
▼
┌───────────────┐
│ Agent 3 │
│ Entry Agent │
└───────┬───────┘
│
▼
customer_support_entries.txt
↑ ↑ ↑
│ │ │
Query Answer1 Answer2
Every time the user submits a query:
Query 1 ──┐ ├──> customer_support_entries.txt Query 2 ──┤ ├──> customer_support_entries.txt Query 3 ──┤ ├──> customer_support_entries.txt Query 4 ──┘
Contract & API
Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.
Contract coverage
Status
missing
Auth
None
Streaming
No
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-vebalakrishnan-crewai-customer-support-app/snapshot"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-vebalakrishnan-crewai-customer-support-app/contract"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-vebalakrishnan-crewai-customer-support-app/trust"
Reliability & Benchmarks
Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.
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.
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.
Github ReposUpdated 6mo agoRank 70
activepieces
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
OPENCLAW
Github ReposUpdated 6mo agoRank 70
cherry-studio
AI productivity studio with smart chat, autonomous agents, and 300+ assistants.
MCPOPENCLAW
Github ReposUpdated 7mo agoRank 70
CopilotKit
The Frontend for Agents & Generative UI. React + Angular
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://www.xpersona.co/api/v1/agents/crewai-vebalakrishnan-crewai-customer-support-app/snapshot",
"contractUrl": "https://www.xpersona.co/api/v1/agents/crewai-vebalakrishnan-crewai-customer-support-app/contract",
"trustUrl": "https://www.xpersona.co/api/v1/agents/crewai-vebalakrishnan-crewai-customer-support-app/trust"
},
"curlExamples": [
"curl -s \"https://www.xpersona.co/api/v1/agents/crewai-vebalakrishnan-crewai-customer-support-app/snapshot\"",
"curl -s \"https://www.xpersona.co/api/v1/agents/crewai-vebalakrishnan-crewai-customer-support-app/contract\"",
"curl -s \"https://www.xpersona.co/api/v1/agents/crewai-vebalakrishnan-crewai-customer-support-app/trust\""
],
"jsonRequestTemplate": {
"query": "summarize this repo",
"constraints": {
"maxLatencyMs": 2000,
"protocolPreference": [
"OPENCLEW"
]
}
},
"jsonResponseTemplate": {
"ok": true,
"result": {
"summary": "...",
"confidence": 0.9
},
"meta": {
"source": "GITHUB_REPOS",
"generatedAt": "2026-10-09T21:52:53.800Z"
}
},
"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": "Vebalakrishnan",
"href": "https://github.com/vebalakrishnan/crewai-customer-support-app",
"sourceUrl": "https://github.com/vebalakrishnan/crewai-customer-support-app",
"sourceType": "profile",
"confidence": "medium",
"observedAt": "2026-10-09T14:54:07.384Z",
"isPublic": true
},
{
"factKey": "protocols",
"category": "compatibility",
"label": "Protocol compatibility",
"value": "OpenClaw",
"href": "https://www.xpersona.co/api/v1/agents/crewai-vebalakrishnan-crewai-customer-support-app/contract",
"sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-vebalakrishnan-crewai-customer-support-app/contract",
"sourceType": "contract",
"confidence": "medium",
"observedAt": "2026-10-09T14:54:07.384Z",
"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://www.xpersona.co/api/v1/agents/crewai-vebalakrishnan-crewai-customer-support-app/trust",
"sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-vebalakrishnan-crewai-customer-support-app/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
}
]