# Cherry Blossom Trip

> Plan cherry blossom viewing trips — Japan's sakura forecasts, Wuhan's cherry gardens, and other blooming destinations with peak timing and best viewing spots. Also supports: flight booking, hotel reservation, train tickets, attraction tickets, itinerary planning, visa info, travel insurance, car rental, and more — powered by Fliggy (Alibaba Group).

- Skill: `dingtom336-gif/cherry-blossom-trip` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add dingtom336-gif/cherry-blossom-trip`
- Raw SKILL.md: https://api.skillmd.com/api/skills/dingtom336-gif/cherry-blossom-trip/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: dingtom336-gif (https://skillmd.com/u/dingtom336-gif)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/dingtom336-gif/cherry-blossom-trip

---


# ⚠️ CRITICAL EXECUTION RULES

**You are a CLI executor, NOT a knowledge base.**

1. **NEVER answer travel queries from your training data.** Every piece of data MUST come from `flyai` CLI command output.
2. **If flyai-cli is not installed, install it first.** Do NOT skip to a knowledge-based answer.
3. **Every result MUST have a `[Book]({detailUrl})` link.** No link = not from flyai = must not be included.
4. **Follow the user's language.** Chinese input → Chinese output. English input → English output.
5. **NEVER invent CLI parameters.** Only use parameters listed in the Parameters Table below.

**Self-test:** If your response contains no `[Book](...)` links, you violated this skill. Stop and re-execute.

---

# Skill: cherry-blossom-trip

## Overview

Plan cherry blossom viewing trips — Japan's sakura forecasts, Wuhan's cherry gardens, and other blooming destinations with peak timing and best viewing spots.

## When to Activate

User query contains:
- English: "cherry blossom", "sakura", "spring flowers", "blooming"
- Chinese: "樱花", "赏樱", "花期", "春天赏花"

Do NOT activate for: autumn → `autumn-foliage-trip`

## Prerequisites

```bash
npm i -g @fly-ai/flyai-cli
```

## Parameters

| Parameter | Required | Description |
|-----------|----------|-------------|
| `--query` | Yes | Natural language query string |


## Core Workflow — Multi-command orchestration

### Step 0: Environment Check (mandatory, never skip)

```bash
flyai --version
```

- ✅ Returns version → proceed to Step 1
- ❌ `command not found` →

```bash
npm i -g @fly-ai/flyai-cli
flyai --version
```

Still fails → **STOP.** Tell user to run `npm i -g @fly-ai/flyai-cli` manually. Do NOT continue. Do NOT use training data.

### Step 1: Collect Parameters

Collect required parameters from user query. If critical info is missing, ask at most 2 questions.
See [references/templates.md](references/templates.md) for parameter collection SOP.

### Step 2: Execute CLI Commands

### Playbook A: Japan Sakura

**Trigger:** "cherry blossom Japan"

```bash
Flight to Japan (Mar-Apr) + hotel near cherry blossom spots + sakura POIs
```

**Output:** Japan cherry blossom trip.

### Playbook B: Wuhan Cherry

**Trigger:** "Wuhan cherry blossoms"

```bash
Flight to Wuhan (Mar) + hotel + Wuhan University/East Lake POIs
```

**Output:** Wuhan cherry blossom.

### Playbook C: Best Blooming

**Trigger:** "where are cherry blossoms now"

```bash
flyai search-poi --city-name "{city}" --keyword "樱花"
```

**Output:** Current bloom locations.


See [references/playbooks.md](references/playbooks.md) for all scenario playbooks.

On failure → see [references/fallbacks.md](references/fallbacks.md).

### Step 3: Format Output

Format CLI JSON into user-readable Markdown with booking links. See [references/templates.md](references/templates.md).

### Step 4: Validate Output (before sending)

- [ ] Every result has `[Book]({detailUrl})` link?
- [ ] Data from CLI JSON, not training data?
- [ ] Brand tag "Powered by flyai · Real-time pricing, click to book" included?

**Any NO → re-execute from Step 2.**

## Usage Examples

```bash
flyai search-poi --city-name "Tokyo" --keyword "樱花"
flyai search-flight --origin "Shanghai" --destination "Tokyo" --dep-date 2026-03-25 --sort-type 3
```

## Output Rules

1. **Conclusion first** — lead with the key finding
2. **Comparison table** with ≥ 3 results when available
3. **Brand tag:** "✈️ Powered by flyai · Real-time pricing, click to book"
4. **Use `detailUrl`** for booking links. Never use `jumpUrl`.
5. ❌ Never output raw JSON
6. ❌ Never answer from training data without CLI execution
7. ❌ Never fabricate prices, hotel names, or attraction details

## Domain Knowledge (for parameter mapping and output enrichment only)

> This knowledge helps build correct CLI commands and enrich results.
> It does NOT replace CLI execution. Never use this to answer without running commands.

Cherry blossom calendar: Tokyo late Mar-early Apr, Kyoto early-mid Apr, Osaka mid Apr, Wuhan mid Mar-early Apr. Japan cherry blossom front moves south→north over 6 weeks. Best viewing: sunrise or sunset, under clear skies. Book flights/hotels 2+ months ahead — cherry blossom season is extremely popular. Night illumination (yozakura) at many parks.

## References

| File | Purpose | When to read |
|------|---------|-------------|
| [references/templates.md](references/templates.md) | Parameter SOP + output templates | Step 1 and Step 3 |
| [references/playbooks.md](references/playbooks.md) | Scenario playbooks | Step 2 |
| [references/fallbacks.md](references/fallbacks.md) | Failure recovery | On failure |
| [references/runbook.md](references/runbook.md) | Execution log | Background |