Production-Ready-TripPlanner-Multi-AI-Agents-Project: Production-Ready TripPlanner Multi-AI Agent Project: Transform your travel planning with AI-driven assistance

by shaheennabi · Agent Tool · ★ 79

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Security audit verdict: SAFE · quality 58/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agentic-workflowautomated-flight-searchgenerative-aigptindustry-readylanggraphmodular-codingmulti-ai-agentsmultiagentssystemsopenai

Quick Facts

Stars79
Forks17
LanguageJupyter Notebook
CategoryAgent Tool
LicenseMIT
Quality Score58/100
Last Updated2025-03-04
Created2024-11-17
Est. Tokens~19k

About Production-Ready-TripPlanner-Multi-AI-Agents-Project

🌺 🌿 🌱 Production-Ready TripPlanner Multi-AI Agents Project 🍃 🌸 🪴 Discussions box is open, you can ask anything & i will accept any pull request feel free to contribute (you can later use this project in your resume etc..) Problem Statement Note: This project simulates an industry-standard scenario where I am assuming the role of a developer at XYZ Company.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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