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Trip Map Builder

Community
hiyeshu
trip-map-builder

End-to-end trip planning: gather user constraints, build a reference itinerary, research locations and dining signals via 大众点评 + 小红书, then generate an interactive mobile-first map page (Leaflet + timeline) and optionally deploy to Vercel. Use when user asks to plan a trip, create an itinerary, research restaurants on 大众点评/小红书, build a trip map page, or says "行程规划", "行程地图", "trip map", "plan my trip", "做个行程". Covers the full pipeline from scattered inputs (screenshots, wishlists) to a deployable reference map with navigation links, 小红书 links, payment info, and reservation buttons.

Overview

Publisherhiyeshu
Repositorytrip-map-builder
Skill nametrip-map-builder
Stars
246
Forks
26
Bundled files
6
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by hiyeshu on GitHub. Read the source before you install it.

Installation

Install the Trip Map Builder AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/hiyeshu/trip-map-builder/tree/main
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/hiyeshu/trip-map-builder.git \
  .claude/skills/trip-map-builder
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Trip Map Builder in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Trip Map Builder on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Trip Map Builder is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Trip Map Builder

Three-phase pipeline: Plan → Research → Build.

The output is a reference itinerary, not a script the traveler must obey. During the trip, weather, current location, fatigue, and hunger can override the original plan.

Shared memory

Before planning or building, read ~/.trip-map-builder/MEMORY.md if it exists. Use it only for durable traveler context:

  • pace preference
  • food and drink preferences
  • budget habits
  • payment and navigation preferences
  • previously generated trip outputs
  • recurring constraints and unresolved follow-ups

If the file does not exist, continue normally. Do not block on memory setup.

Do not store raw screenshots, passport data, booking codes, full chat logs, or other sensitive/private material.

After each completed trip plan, research pass, or map build, update ~/.trip-map-builder/MEMORY.md with only durable facts:

md
# Trip Map Builder Memory

## Traveler Defaults
- Departure city:
- Pace:
- Food preferences:
- Budget habits:
- Payment preference:
- Navigation preference:
- Language preference:

## Past Trips
| Trip | Dates | Destination | Output | Notes |
|------|-------|-------------|--------|-------|

## Reusable Preferences
-

## Open Threads
-

Phase 1: Plan the itinerary

Read references/trip-planning.md for the full methodology.

Core sequence:

  1. Extract hard constraints — dates, flight times, terminals, hotel location
  2. Group user's wishlist — city-easy / needs-reservation / far-suburbs / pass-through
  3. Cut high-risk items first — too far, holiday-crowded, weather-dependent. Say what was cut and why.
  4. Arrange by area — one main area per day, first day light, last day close to airport
  5. Fill in meals — daily-area candidates first, 大众点评 + 小红书 signals second, fame last.
  6. Add tickets & transport — only critical ones (museum tickets, airport transfer)
  7. Write reference doc — conclusion first, then daily plan, weather-sensitive spots, meal areas, and what was cut

Key principles:

  • Not everything the user listed fits. Delete for them.
  • One area per day. One reservation-required spot per day max.
  • Itineraries should be smooth, not packed.
  • The plan gives coordinates for later adjustment; it does not pretend reality will follow the timeline.
  • All user-facing questions follow the 4-beat format: Re-ground → Simplify → Recommend → Options. See references/trip-planning.md § 用户交互 for examples and anti-patterns.

Phase 2: Research via 大众点评 + 小红书

Read references/dianping-research.md for the 大众点评 OpenCLI workflow. Read references/xhs-research.md for the 小红书 OpenCLI + CDP workflow.

For restaurants, use 大众点评 as the main Chinese dining signal for taste, queue risk, value, and obvious traps. Use 小红书 to supplement atmosphere, recent experience, photo-worthiness, and soft warnings. Do not bend a whole day around a famous restaurant unless it is already on the route.

小红书 core sequence:

  1. Launch Chrome with --remote-debugging-port=9223
  2. Connect via OpenCLI's CDPBridge
  3. Navigate to xiaohongshu.com/search_result?keyword=<encoded> (never simulate input box)
  4. Intercept POST /api/sns/web/v1/search/notes response
  5. Pick top 2-3 notes by relevance, open detail pages
  6. Extract via DOM: #detail-title, #detail-desc, .author-container .username
  7. Compress to one decision-useful sentence per store, write back to local .md

Filtering rules:

  • Keep: specific store name, address, dish, personal experience, repeated keywords
  • Drop: generic area roundups, reposts, pure emotion, "氛围很好" x3
  • Output: store name + one representative link + 2-3 sentence verdict

Phase 3: Build the map page

  1. Copy assets/template.html → index.html
  2. Fill HOTEL object and DAYS array with structured data from Phase 1+2
  3. Each location needs: name, lat/lng, type, time, desc; optional: budget, detail, pay, xhs, reserve, gmap
  4. Fill overviewContent() with trip summary, payment warnings
  5. Apply design system — default template uses Apple style, but can switch to any style from awesome-design-md

Location types: food | spot | drink | hotel | transport

Payment chip values: 1 = confirmed yes (green), 0.5 = maybe (orange), omit = not shown

Design system (optional)

Default template uses Apple design system (SF Pro, light theme, frosted glass).

To use a different style, grab a DESIGN.md from awesome-design-md:

bash
# Browse available design systems
# Apple, Vercel, Linear, Stripe, Notion, Airbnb, Nike, Spotify, etc.
curl -O https://raw.githubusercontent.com/VoltAgent/awesome-design-md/main/design-md/<brand>/DESIGN.md

Then adjust template.html's :root CSS variables (colors, fonts, spacing, border-radius) to match the chosen DESIGN.md tokens.

Deploy (optional)

bash
git init && git add . && git commit -m "trip map"
gh repo create REPO --public --source=. --push
# Import from vercel.com/new — auto-deploys on push

Dependencies

ToolPurposeInstall
OpenCLI大众点评 adapter + 小红书调研npm install -g @jackwener/opencli
Chrome/Chromium浏览器 + 远程调试已有
Leaflet.js地图渲染(CDN 引入,无需安装)template.html 内置
gh CLIGitHub 仓库创建(可选)brew install gh

Resources

  • references/trip-planning.md — itinerary planning methodology, input/output templates, selection principles, common pitfalls
  • references/dianping-research.md — 大众点评 OpenCLI search/shop workflow, dining decision signals, writeback format
  • references/xhs-research.md — OpenCLI installation, Chrome CDP setup, 小红书 search workflow, API details, filtering criteria
  • assets/template.html — single-file HTML map template (Leaflet + Apple design system)
  • awesome-design-md — 60+ brand design systems (Apple, Vercel, Stripe, Linear, etc.) for alternative styling

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Trip Map Builder AI skill do?

End-to-end trip planning: gather user constraints, build a reference itinerary, research locations and dining signals via 大众点评 + 小红书, then generate an interactive mobile-first map page (Leaflet + timeline) and optionally deploy to Vercel. Use when user asks to plan a trip, create an itinerary, research restaurants on 大众点评/小红书, build a trip map page, or says "行程规划", "行程地图", "trip map", "plan my trip", "做个行程". Covers the full pipeline from scattered inputs (screenshots, wishlists) to a deployable reference map with navigation links, 小红书 links, payment info, and reservation buttons.

Why use Trip Map Builder on TypingMind?

Because you install it once and use it with any model. Trip Map Builder is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Trip Map Builder in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hiyeshu/trip-map-builder/tree/main. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Trip Map Builder?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Trip Map Builder?

As many as you like. As long as a model supports skills, you can use Trip Map Builder with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Trip Map Builder AI skill free?

It is published on GitHub by hiyeshu. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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