How should logistics-optimization-crewai 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

logistics-optimization-crewai answer-first brief

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 — 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. --- 📖 Table of Contents - $1 - $1 - $1 - Capability contract not published. No trust telemetry is available yet. Last updated 4/15/2026.

Freshness

Last checked 4/15/2026

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 REPOS, runtime-metrics, public facts pack

Card Facts Snapshot Contract Trust

Claim this agent

Agent DossierGITHUB REPOSSafety: 66/100

logistics-optimization-crewai

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

Sanjai S0

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Unpublished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

Sanjai S0

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

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/
├── Flow/                  # Workflow diagrams (.mmd)
│   └── workflow.mmd
├── .env                   # Private API keys
├── .env.example           # Environment template
├── .gitignore             # Git exclusions
├── LICENSE                # MIT License
├── logistics_crew.py      # Main CrewAI implementation
├── 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

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

🚢 Logistics Optimization Analysis — CrewAI

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.

🌟 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.

🏗️ 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

🛠️ Key Features

🤖 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.
📈 Comprehensive Analysis: Covers route efficiency, last-mile delivery, and inventory turnover trends.
📋 Actionable Strategies: Delivers prioritized plans with effort/impact ratings and estimated KPI gains.
🔄 Parametric Execution: Tailor analysis to any product mix (e.g., electronics, perishables, automotive).

💻 Tech Stack

Orchestration: CrewAI
LLM: Google Gemini 2.5 Flash
Language: Python 3.10+
Environment: python-dotenv for secret management

📂 Project Structure

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

⚙️ 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

Get your Gemini API Key from Google AI Studio.
Setup environment:
```
cp .env.example .env
```

Edit .env and add your key:

GEMINI_API_KEY=your_gemini_api_key_here

🚀 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:

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

📜 License

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

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

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-sanjai-s0-logistics-optimization-crewai/snapshot"

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

curl -s "https://xpersona.co/api/v1/agents/crewai-sanjai-s0-logistics-optimization-crewai/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-sanjai-s0-logistics-optimization-crewai/snapshot",
    "contractUrl": "https://xpersona.co/api/v1/agents/crewai-sanjai-s0-logistics-optimization-crewai/contract",
    "trustUrl": "https://xpersona.co/api/v1/agents/crewai-sanjai-s0-logistics-optimization-crewai/trust"
  },
  "curlExamples": [
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-sanjai-s0-logistics-optimization-crewai/snapshot\"",
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-sanjai-s0-logistics-optimization-crewai/contract\"",
    "curl -s \"https://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_REPOS",
      "generatedAt": "2026-04-17T01:27:12.479Z"
    }
  },
  "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": "Sanjai S0",
    "href": "https://github.com/SANJAI-s0/logistics-optimization-crewai",
    "sourceUrl": "https://github.com/SANJAI-s0/logistics-optimization-crewai",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-04-15T06:04:19.445Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://xpersona.co/api/v1/agents/crewai-sanjai-s0-logistics-optimization-crewai/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/crewai-sanjai-s0-logistics-optimization-crewai/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-04-15T06:04:19.445Z",
    "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-sanjai-s0-logistics-optimization-crewai/trust",
    "sourceUrl": "https://xpersona.co/api/v1/agents/crewai-sanjai-s0-logistics-optimization-crewai/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
  }
]