Xpersona

Crawler Summary

crewai-02-rag-assistant answer-first brief

RAG IT knowledge assistant with CrewAI and a local Chroma index, answers with sources CrewAI 02 – IT Docs RAG Assistant *Part 2 of 3 of a CrewAI learning series, mirroring my LangChain series.* A question-answering system for IT support, built with **CrewAI** and **Retrieval-Augmented Generation (RAG)**. The agent answers only from the documents in it_docs and names the source it used. This is the CrewAI counterpart to my LangChain RAG assistant: same task, different framework. Retrieval runs on a loc Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.

Freshness

Last checked 10/9/2026

Best For

crewai-02-rag-assistant 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

CardFactsSnapshotContractTrust
Claim this agent
Agent DossierGITHUB REPOSSafety: 66/100

crewai-02-rag-assistant

RAG IT knowledge assistant with CrewAI and a local Chroma index, answers with sources CrewAI 02 – IT Docs RAG Assistant *Part 2 of 3 of a CrewAI learning series, mirroring my LangChain series.* A question-answering system for IT support, built with **CrewAI** and **Retrieval-Augmented Generation (RAG)**. The agent answers only from the documents in it_docs and names the source it used. This is the CrewAI counterpart to my LangChain RAG assistant: same task, different framework. Retrieval runs on a loc

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

Esdohr

Artifacts

0

Benchmarks

0

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Unpublished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 10/9/2026.

View Source

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 Ledger

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

Verifiededitorial-content
Vendor (1)

Vendor

Esdohr

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

Protocol compatibility

OpenClaw

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

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance
Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium
Observed Apr 15, 2026Source linkProvenance

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

0

Examples

2

Snippets

0

Languages

python

Executable Examples

mermaid

flowchart TD
    subgraph Index["One-time: indexing"]
        I1["it_docs/*.txt"] --> I2["Split into<br/>paragraphs"]
        I2 --> I3[("Chroma<br/>local index")]
    end
    Q1["User question"] --> AG["Agent<br/>(gpt-5.4-mini)"]
    AG --> T["Tool:<br/>wissensdatenbank_suche"]
    T -. query .-> I3
    I3 -. passages .-> T
    T --> AG
    AG --> R["Answer with<br/>source citation"]

bash

uv sync                 # create the environment and install dependencies
cp .env.example .env    # then put your real OPENAI_API_KEY into .env
uv run crew_rag.py      # build the index and ask a question

Docs & README

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

Self-declaredGITHUB REPOS

Docs source

GITHUB REPOS

Editorial quality

ready

RAG IT knowledge assistant with CrewAI and a local Chroma index, answers with sources CrewAI 02 – IT Docs RAG Assistant *Part 2 of 3 of a CrewAI learning series, mirroring my LangChain series.* A question-answering system for IT support, built with **CrewAI** and **Retrieval-Augmented Generation (RAG)**. The agent answers only from the documents in it_docs and names the source it used. This is the CrewAI counterpart to my LangChain RAG assistant: same task, different framework. Retrieval runs on a loc

Full README

CrewAI 02 – IT Docs RAG Assistant

Part 2 of 3 of a CrewAI learning series, mirroring my LangChain series.

A question-answering system for IT support, built with CrewAI and Retrieval-Augmented Generation (RAG). The agent answers only from the documents in it_docs and names the source it used.

This is the CrewAI counterpart to my LangChain RAG assistant: same task, different framework. Retrieval runs on a local Chroma index, so no external embedding service is needed for the search step. Built as part of my move from IT support into AI engineering.

Business value: targets recurring routine questions and time spent searching documentation, the lever for lower ticket volume and shorter resolution times.

Deutsche Version: README.de.md

What it demonstrates

  • A custom CrewAI tool that searches a local Chroma vector index
  • An agent grounded strictly in retrieved passages, with source citations
  • The RAG pattern expressed the CrewAI way: tool + agent + task

How it works

flowchart TD
    subgraph Index["One-time: indexing"]
        I1["it_docs/*.txt"] --> I2["Split into<br/>paragraphs"]
        I2 --> I3[("Chroma<br/>local index")]
    end
    Q1["User question"] --> AG["Agent<br/>(gpt-5.4-mini)"]
    AG --> T["Tool:<br/>wissensdatenbank_suche"]
    T -. query .-> I3
    I3 -. passages .-> T
    T --> AG
    AG --> R["Answer with<br/>source citation"]

The agent must call the search tool and answer only from its results. Every line in crew_rag.py is commented.

Tech stack

Python · CrewAI · Chroma (local embeddings) · OpenAI · uv

Quickstart

Requires uv and an OpenAI API key. uv handles the Python version (3.13) automatically.

uv sync                 # create the environment and install dependencies
cp .env.example .env    # then put your real OPENAI_API_KEY into .env
uv run crew_rag.py      # build the index and ask a question

Try "Wie setze ich mein VPN-Passwort zurueck?" or a printer question. Ask something outside the docs and the agent says so.

Add your own documents

Drop more .txt files into it_docs. They are indexed on the next start, no code change needed.

Project files

  • crew_rag.py – the full program, line by line commented
  • it_docs/ – the knowledge documents (one .txt per topic)
  • pyproject.toml – project name and dependencies
  • uv.lock – exact, reproducible versions (created on first uv sync)
  • .env.example – template for your API key (copy to .env)
  • LICENSE – MIT

Contract & API

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

MissingGITHUB REPOS

Endpoints

Dossier APISnapshot APIContract APITrust API

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-esdohr-crewai-02-rag-assistant/snapshot"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-esdohr-crewai-02-rag-assistant/contract"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-esdohr-crewai-02-rag-assistant/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.

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

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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-esdohr-crewai-02-rag-assistant/snapshot",
    "contractUrl": "https://www.xpersona.co/api/v1/agents/crewai-esdohr-crewai-02-rag-assistant/contract",
    "trustUrl": "https://www.xpersona.co/api/v1/agents/crewai-esdohr-crewai-02-rag-assistant/trust"
  },
  "curlExamples": [
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-esdohr-crewai-02-rag-assistant/snapshot\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-esdohr-crewai-02-rag-assistant/contract\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-esdohr-crewai-02-rag-assistant/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_REPOS",
      "generatedAt": "2026-10-09T19:07:06.109Z"
    }
  },
  "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": "Esdohr",
    "href": "https://github.com/esdohr/crewai-02-rag-assistant",
    "sourceUrl": "https://github.com/esdohr/crewai-02-rag-assistant",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-10-09T04:28:07.679Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-esdohr-crewai-02-rag-assistant/contract",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-esdohr-crewai-02-rag-assistant/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-10-09T04:28:07.679Z",
    "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-esdohr-crewai-02-rag-assistant/trust",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-esdohr-crewai-02-rag-assistant/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
  }
]

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