Back to Skills

itinerary-optimizer

OneWave-AI
Updated Today
13 views
11
4
11
View on GitHub
Otherapi

About

The itinerary-optimizer skill generates efficient, multi-stop travel itineraries with integrated time management. It handles routing optimization, schedules transportation and reservations, and allocates buffer time for flexibility. Developers should use this to automate the creation of realistic daily plans that balance structure with spontaneity for end-users.

Documentation

Itinerary Optimizer

Efficiently route multi-stop trips with time management. Include transportation, restaurant/activity reservations timeline, and buffer time for spontaneity.

Instructions

You are an expert travel planner and logistics optimizer. Create efficient, realistic itineraries that don't overpack days. Include: routing optimization, realistic time allocations, transportation between locations, reservation timing, buffer for spontaneity, and backup plans. Balance structure with flexibility.

Output Format

# Itinerary Optimizer Output

**Generated**: {timestamp}

---

## Results

[Your formatted output here]

---

## Recommendations

[Actionable next steps]

Best Practices

  1. Be Specific: Focus on concrete, actionable outputs
  2. Use Templates: Provide copy-paste ready formats
  3. Include Examples: Show real-world usage
  4. Add Context: Explain why recommendations matter
  5. Stay Current: Use latest best practices for travel

Common Use Cases

Trigger Phrases:

  • "Help me with [use case]"
  • "Generate [output type]"
  • "Create [deliverable]"

Example Request:

"[Sample user request here]"

Response Approach:

  1. Understand user's context and goals
  2. Generate comprehensive output
  3. Provide actionable recommendations
  4. Include examples and templates
  5. Suggest next steps

Remember: Focus on delivering value quickly and clearly!

Quick Install

/plugin add https://github.com/OneWave-AI/claude-skills/tree/main/itinerary-optimizer

Copy and paste this command in Claude Code to install this skill

GitHub 仓库

OneWave-AI/claude-skills
Path: itinerary-optimizer

Related Skills

evaluating-llms-harness

Testing

This Claude Skill runs the lm-evaluation-harness to benchmark LLMs across 60+ standardized academic tasks like MMLU and GSM8K. It's designed for developers to compare model quality, track training progress, or report academic results. The tool supports various backends including HuggingFace and vLLM models.

View skill

langchain

Meta

LangChain is a framework for building LLM applications using agents, chains, and RAG pipelines. It supports multiple LLM providers, offers 500+ integrations, and includes features like tool calling and memory management. Use it for rapid prototyping and deploying production systems like chatbots, autonomous agents, and question-answering services.

View skill

huggingface-accelerate

Development

HuggingFace Accelerate provides the simplest API for adding distributed training to PyTorch scripts with just 4 lines of code. It offers a unified interface for multiple distributed training frameworks like DeepSpeed, FSDP, and DDP while handling automatic device placement and mixed precision. This makes it ideal for developers who want to quickly scale their PyTorch training across multiple GPUs or nodes without complex configuration.

View skill

nestjs

Meta

This skill provides NestJS development standards and architectural patterns for building domain-centric applications. It covers modular design, dependency injection, decorator patterns, and key framework features like controllers, services, middleware, and interceptors. Use it when developing NestJS applications, implementing APIs, configuring microservices, or integrating with databases.

View skill