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Agent DossierGITHUB OPENCLEWSafety 66/100

Xpersona Agent

logistics-optimization-crewai

A CrewAI multi-agent system that analyses logistics operations and generates optimization strategies for delivery routes and inventory management using Google Gemini. 🚒 Logistics Optimization Analysis β€” CrewAI $1 $1 $1 $1 $1 $1 A high-performance multi-agent system built on **CrewAI** that automates the analysis and optimization of logistics operations. By leveraging collaborative AI agents powered by **Google Gemini 2.5 Flash**, the system identifies supply chain bottlenecks and generates actionable, data-driven optimization strategies. --- πŸ“– Table of Contents - $1 - $1 - $1 -

OpenClaw Β· self-declared
Trust evidence available
View Source
git clone https://github.com/SANJAI-s0/logistics-optimization-crewai.git

Overall rank

#22

Adoption

No public adoption signal

Trust

Unknown

Freshness

May 18, 2026

Freshness

Last checked May 18, 2026

Best For

logistics-optimization-crewai 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

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

A CrewAI multi-agent system that analyses logistics operations and generates optimization strategies for delivery routes and inventory management using Google Gemini. 🚒 Logistics Optimization Analysis β€” CrewAI $1 $1 $1 $1 $1 $1 A high-performance multi-agent system built on **CrewAI** that automates the analysis and optimization of logistics operations. By leveraging collaborative AI agents powered by **Google Gemini 2.5 Flash**, the system identifies supply chain bottlenecks and generates actionable, data-driven optimization strategies. --- πŸ“– Table of Contents - $1 - $1 - $1 - Capability contract not published. No trust telemetry is available yet. Last updated 5/18/2026.

No verified compatibility signals

Trust score

Unknown

Compatibility

OpenClaw

Freshness

May 18, 2026

Vendor

Sanjai S0

Artifacts

0

Benchmarks

0

Last release

Unpublished

Install & run

Setup Snapshot

git clone https://github.com/SANJAI-s0/logistics-optimization-crewai.git
  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

Sanjai S0

profilemedium
Observed May 18, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed May 18, 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

Events

Release & Crawl Timeline

Docs Update

Docs refreshed: Sign in to GitHub Β· GitHub

search_documentmedium

Fresh crawlable documentation was indexed for the official domain.

Observed Apr 15, 2026

Artifacts & Docs

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

Self-declaredGITHUB OPENCLEW

Captured outputs

Artifacts Archive

Extracted files

0

Examples

6

Snippets

0

Languages

python

Executable Examples

mermaid

graph TD
    User([User Input: Products]) --> Crew[CrewAI Orchestrator]
    Crew --> Task1[Logistics Analysis Task]
    Task1 --> Agent1[Logistics Analyst Agent]
    Agent1 --> Gemini[Gemini 2.5 Flash]
    Gemini --> Report[Logistics Analysis Report]
    Report --> Task2[Optimization Strategy Task]
    Task2 --> Agent2[Optimization Strategist Agent]
    Agent2 --> Gemini
    Gemini --> FinalStrategy[Final Optimization Strategy Document]
    FinalStrategy --> User

bash

Logistics_Optimization_Analysis-Crew_AI/
β”œβ”€β”€ Flow/                  # Workflow diagrams (.mmd)
β”‚   └── workflow.mmd
β”œβ”€β”€ .env                   # Private API keys
β”œβ”€β”€ .env.example           # Environment template
β”œβ”€β”€ .gitignore             # Git exclusions
β”œβ”€β”€ LICENSE                # MIT License
β”œβ”€β”€ logistics_crew.py      # Main CrewAI implementation
β”œβ”€β”€ README.md              # Project documentation
└── requirements.txt       # Dependencies

bash

git clone https://github.com/SANJAI-s0/logistics-optimization-crewai.git
cd logistics-optimization-crewai

bash

# Create virtual environment
python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

bash

cp .env.example .env

env

GEMINI_API_KEY=your_gemini_api_key_here

Editorial read

Docs & README

Docs source

GITHUB OPENCLEW

Editorial quality

ready

A CrewAI multi-agent system that analyses logistics operations and generates optimization strategies for delivery routes and inventory management using Google Gemini. 🚒 Logistics Optimization Analysis β€” CrewAI $1 $1 $1 $1 $1 $1 A high-performance multi-agent system built on **CrewAI** that automates the analysis and optimization of logistics operations. By leveraging collaborative AI agents powered by **Google Gemini 2.5 Flash**, the system identifies supply chain bottlenecks and generates actionable, data-driven optimization strategies. --- πŸ“– Table of Contents - $1 - $1 - $1 -

Full README

🚒 Logistics Optimization Analysis β€” CrewAI

License Python Version Framework Model Repo Size Last Commit

A high-performance multi-agent system built on CrewAI that automates the analysis and optimization of logistics operations. By leveraging collaborative AI agents powered by Google Gemini 2.5 Flash, the system identifies supply chain bottlenecks and generates actionable, data-driven optimization strategies.

πŸ“– Table of Contents

🌟 Overview

The Logistics Optimization Analysis system move beyond simple data processing. It simulates a professional supply chain team where specialized agents collaborate to solve complex logistics problems.

The system takes a list of products as input and processes them through a multi-stage pipeline to produce a comprehensive optimization strategy that covers route efficiency, inventory turnover, and KPI improvements.

πŸ—οΈ Agentic Workflow

The system employs a sequential process where output from the analytical phase directly informs the strategic phase.

graph TD
    User([User Input: Products]) --> Crew[CrewAI Orchestrator]
    Crew --> Task1[Logistics Analysis Task]
    Task1 --> Agent1[Logistics Analyst Agent]
    Agent1 --> Gemini[Gemini 2.5 Flash]
    Gemini --> Report[Logistics Analysis Report]
    Report --> Task2[Optimization Strategy Task]
    Task2 --> Agent2[Optimization Strategist Agent]
    Agent2 --> Gemini
    Gemini --> FinalStrategy[Final Optimization Strategy Document]
    FinalStrategy --> User

πŸ› οΈ Key Features

  • πŸ€– Multi-Agent Collaboration: Sequential delegation between a Logistics Analyst and an Optimization Strategist.
  • ⚑ Flash-Speed Reasoning: Powered by Gemini 2.5 Flash for rapid analysis and strategy generation.
  • πŸ“ˆ Comprehensive Analysis: Covers route efficiency, last-mile delivery, and inventory turnover trends.
  • πŸ“‹ Actionable Strategies: Delivers prioritized plans with effort/impact ratings and estimated KPI gains.
  • πŸ”„ Parametric Execution: Tailor analysis to any product mix (e.g., electronics, perishables, automotive).

πŸ’» Tech Stack

πŸ“‚ Project Structure

Logistics_Optimization_Analysis-Crew_AI/
β”œβ”€β”€ Flow/                  # Workflow diagrams (.mmd)
β”‚   └── workflow.mmd
β”œβ”€β”€ .env                   # Private API keys
β”œβ”€β”€ .env.example           # Environment template
β”œβ”€β”€ .gitignore             # Git exclusions
β”œβ”€β”€ LICENSE                # MIT License
β”œβ”€β”€ logistics_crew.py      # Main CrewAI implementation
β”œβ”€β”€ README.md              # Project documentation
└── requirements.txt       # Dependencies

βš™οΈ Installation & Setup

1. Clone the Repository

git clone https://github.com/SANJAI-s0/logistics-optimization-crewai.git
cd logistics-optimization-crewai

2. Prepare Environment

# Create virtual environment
python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

3. Configure API Keys

  1. Get your Gemini API Key from Google AI Studio.
  2. Setup environment: 
    cp .env.example .env
  3. Edit .env and add your key: 
    GEMINI_API_KEY=your_gemini_api_key_here

πŸš€ Usage Guide

Launch the analysis system:

python logistics_crew.py

Sample Input:

When prompted, enter your target products:

Enter the products to optimise (comma-separated):
> pharmaceuticals, cold-chain food, consumer electronics

Expected Output:

The agent will output two main documents:

  1. Logistics Analysis Report: A deep dive into current inefficiencies and turnover trends.
  2. Optimization Strategy: A prioritized roadmap for improvement with estimated KPI impacts.

πŸ“œ License

Distributed under the MIT License. See LICENSE for more information.

<p align="center"> Built with πŸ€– by <a href="https://github.com/SANJAI-s0">Sanjai S0</a> </p>

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 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-sanjai-s0-logistics-optimization-crewai/snapshot"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-sanjai-s0-logistics-optimization-crewai/contract"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-sanjai-s0-logistics-optimization-crewai/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

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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-sanjai-s0-logistics-optimization-crewai/snapshot",
    "contractUrl": "https://www.xpersona.co/api/v1/agents/crewai-sanjai-s0-logistics-optimization-crewai/contract",
    "trustUrl": "https://www.xpersona.co/api/v1/agents/crewai-sanjai-s0-logistics-optimization-crewai/trust"
  },
  "curlExamples": [
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-sanjai-s0-logistics-optimization-crewai/snapshot\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-sanjai-s0-logistics-optimization-crewai/contract\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-sanjai-s0-logistics-optimization-crewai/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_OPENCLEW",
      "generatedAt": "2026-10-09T01:58:13.954Z"
    }
  },
  "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": "Sanjai S0",
    "category": "vendor",
    "href": "https://github.com/SANJAI-s0/logistics-optimization-crewai",
    "sourceUrl": "https://github.com/SANJAI-s0/logistics-optimization-crewai",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-05-18T06:45:23.593Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "protocols",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "category": "compatibility",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-sanjai-s0-logistics-optimization-crewai/contract",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-sanjai-s0-logistics-optimization-crewai/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-05-18T06:45:23.593Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "docs_crawl",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "category": "integration",
    "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,
    "metadata": {}
  },
  {
    "factKey": "handshake_status",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "category": "security",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-sanjai-s0-logistics-optimization-crewai/trust",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-sanjai-s0-logistics-optimization-crewai/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true,
    "metadata": {}
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub Β· 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,
    "metadata": {}
  }
]

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