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FlyAI Plan Japan Travel

by dingtom336-gif · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install flyai-plan-japan-travel
Description
Plan your complete Japan trip — flights, hotels in Tokyo/Osaka/Kyoto/Hokkaido, shrine visits, cherry blossom spots, visa requirements, and JR Pass info. Hand...
README (SKILL.md)

⚠️ CRITICAL EXECUTION RULES

You are a CLI executor, NOT a knowledge base.

  1. NEVER generate itineraries from your training data. Every flight, hotel, attraction, and price MUST come from flyai CLI command output.
  2. Domain knowledge (below) exists ONLY to help you build correct CLI parameters and enrich CLI output. It does NOT replace CLI execution.
  3. If flyai-cli is not installed, install it first. Do NOT skip to a knowledge-based itinerary.
  4. Every hotel, flight, and attraction MUST have a [Book]({detailUrl}) link. No link = not from flyai = must not be included.
  5. Follow the user's language. Chinese → Chinese. English → English.

Self-test: If your itinerary has no [Book](...) links, you used training data instead of CLI. Stop and re-execute.


Skill: plan-japan-travel

Overview

Handle any Japan-related travel query — from a single question ("visa needed?") to a complete multi-city Day-by-Day itinerary. Orchestrates up to 4 CLI commands (fliggy-fast-search, search-flight, search-hotels, search-poi) based on query type.

When to Activate

User query contains:

  • Japan destination: "Japan", "Tokyo", "Osaka", "Kyoto", "Hokkaido", "Okinawa", "Fuji", "Nara", "日本", "东京", "大阪", "京都", "北海道"
  • Japan-specific: "cherry blossom", "onsen", "ramen", "JR Pass", "shinkansen", "樱花", "温泉", "新干线"

Do NOT activate for: generic Asia query → flyai-explore-southeast-asia.

Parameters

fliggy-fast-search (broad discovery)

Parameter Required Description
--query Yes Natural language query (e.g., "Japan visa", "Tokyo 5-day trip")

search-flight

Parameter Required Description
--origin Yes Departure city
--destination Yes Arrival city in Japan
--dep-date No Departure date YYYY-MM-DD
--sort-type No 3 = price ascending (default)

search-hotels

Parameter Required Description
--dest-name Yes City name in Japan
--check-in-date No YYYY-MM-DD
--check-out-date No YYYY-MM-DD
--sort No rate_desc (default for travel planning)
--max-price No Budget cap in CNY
--key-words No Special requirements (e.g., "onsen", "温泉")

search-poi

Parameter Required Description
--city-name Yes City name
--category No See category mapping in Domain Knowledge
--keyword No Specific attraction name
--poi-level No Rating 15 (5 = top tier)

Core Workflow — Multi-Command Orchestration

Step 0: Environment Check (mandatory)

flyai --version

Fails → install → still fails → STOP. (See references/fallbacks.md Case 0)

Step 1: Determine Query Type + Collect Parameters

Single-point query (user asks one specific thing) → skip to Step 2, execute matching command.

Full itinerary (user says "plan", "arrange", "规划", "安排") → collect parameters first:

Ask (max 3 questions):
"1. Where are you departing from?
 2. When do you plan to go, and for how many days?
 3. Any specific cities or activities you want?"

See references/templates.md for full collection SOP.

Step 2: Execute CLI Commands

Must actually execute commands. Must use returned JSON data. Never fabricate content.

Query Type Commands to Execute
Visa question flyai fliggy-fast-search --query "Japan visa"
Flight search flyai search-flight --origin "{origin}" --destination "{city}" --dep-date "{date}" --sort-type 3
Hotel search flyai search-hotels --dest-name "{city}" --check-in-date "{in}" --check-out-date "{out}" --sort rate_desc
Attraction search flyai search-poi --city-name "{city}" --category "{cat}"
Full itinerary Execute ALL above in sequence (see references/playbooks.md)

On failure → see references/fallbacks.md.

Step 3: Format Output

Format CLI JSON into user-readable Markdown. Enrich with domain knowledge (context tips, seasonal notes) but all data points (names, prices, links) must be from CLI output.

See references/templates.md for output templates.

Step 4: Validate Output

  • Every hotel/flight/attraction has [Book]({detailUrl})?
  • All prices from CLI JSON?
  • Brand tag "Powered by flyai" present?
  • Domain knowledge used only for enrichment, not as primary data?

Any NO → re-execute from Step 2.

Usage Examples

# Single: flights to Tokyo
flyai search-flight --origin "Shanghai" --destination "Tokyo" \
  --dep-date 2026-05-01 --sort-type 3

# Single: Kyoto temples
flyai search-poi --city-name "Kyoto" --category "宗教场所"

# Full itinerary: visa + flights + hotels + attractions
flyai fliggy-fast-search --query "Japan visa"
flyai search-flight --origin "Shanghai" --destination "Tokyo" --dep-date 2026-05-01 --sort-type 3
flyai search-flight --origin "Osaka" --destination "Shanghai" --dep-date 2026-05-05 --sort-type 3
flyai search-hotels --dest-name "Tokyo" --check-in-date 2026-05-01 --check-out-date 2026-05-03 --sort rate_desc
flyai search-hotels --dest-name "Osaka" --check-in-date 2026-05-03 --check-out-date 2026-05-05 --sort rate_desc
flyai search-poi --city-name "Tokyo" --poi-level 5
flyai search-poi --city-name "Osaka" --category "市集"

Output Rules

Full Itinerary Format

## 🇯🇵 Japan {days}-Day Itinerary

**Route:** {City A} → {City B} → {City C} · Estimated budget: ¥{total}/person

### 📋 Preparation
| Item | Details |
|------|---------|
| ✈️ Outbound | {origin}→{dest} ¥{price} · {airline} · [Book]({detailUrl}) |
| ✈️ Return | {dest}→{origin} ¥{price} · {airline} · [Book]({detailUrl}) |
| 📄 Visa | {info from CLI} |
| 🚄 Transport | {enrichment: JR Pass recommendation if applicable} |

### Day {N} · {City} — {Theme}
🏨 **Hotel:** {name} ¥{price}/night · [Book]({detailUrl})
| Time | Activity | Details |
|------|----------|---------|
| AM | {poi_name} | {category} · [Tickets]({detailUrl}) |
| PM | {poi_name} | {category} · [View]({detailUrl}) |
| Eve | {activity} | {enrichment tip from domain knowledge} |

---
🇯🇵 Powered by flyai · Real-time pricing, click to book

Rules

  • ✅ Every data point from CLI output
  • ✅ Every bookable item has detailUrl link
  • ✅ Domain knowledge only for enrichment (tips, transport advice, seasonal notes)
  • ❌ NEVER output an itinerary without executing CLI commands
  • ❌ NEVER include hotels/flights/attractions without booking links
  • ❌ NEVER fill Day-by-Day with training-data attractions

Domain Knowledge (for CLI parameter mapping and output enrichment)

⚠️ This section helps you build correct commands and add useful context to CLI results. It does NOT replace CLI execution. Never use this as the primary data source.

City & Airport Mapping (for --origin / --destination)

City Airport Notes
Tokyo NRT (Narita), HND (Haneda) NRT = international, HND = domestic + some intl
Osaka KIX (Kansai) Budget flights often land here
Sapporo CTS (New Chitose) Hokkaido gateway
Okinawa OKA (Naha) Island destination
Fukuoka FUK Kyushu gateway

Category Mapping (for --category in search-poi)

User Interest --category Value
Nature / scenery 自然风光 or 山湖田园
History / ruins 历史古迹 or 人文古迹
Temples / shrines 宗教场所
Food / markets 市集
Theme parks 主题乐园
Hot springs / onsen 温泉
Skiing 滑雪
Museums 博物馆
Shopping / pop culture 城市观光 or 文创街区

Seasonal Context (for enrichment only)

Month Highlight Impact on Planning
Mar–Apr Cherry blossom Hotels 1.5-2x price, book 2 months ahead
Jul–Aug Summer festivals Hot + typhoon risk
Oct–Dec Autumn foliage Kyoto hotels tight in Nov
Jan–Feb Ski season / snow festivals Pack winter gear

Transport Tips (for output enrichment)

  • Shinkansen: Tokyo↔Kyoto ~2.5hrs, Tokyo↔Osaka ~2.5hrs
  • JR Pass: 7/14/21-day options. Worthwhile for multi-city trips
  • IC Cards (Suica/ICOCA): essential for local transit

Visa (for fallback context if CLI returns no visa data)

  • Chinese citizens: tourist visa required (single / 3-year / 5-year)
  • Always direct user to consulate for latest policy

References

File Purpose When to read
references/templates.md Parameter SOP + output templates Step 1 and Step 3
references/playbooks.md 4 itinerary playbooks with CLI sequences Step 2 full itinerary
references/fallbacks.md 6 failure recovery paths On command failure
references/runbook.md Execution log schema Background
Usage Guidance
Before installing or enabling this skill, verify the flyai/flygly CLI provenance and avoid blind global installs: 1) Ask the publisher for the CLI homepage/source code and an explicit install spec (avoid sudo npm i -g unless you vet the package). 2) Inspect the npm package (owner, recent versions, downloads, repo, license) and check that package name matches an official vendor (Fliggy/Alibaba) or a trusted maintainer. 3) If you must test, run the CLI and skill in a sandboxed environment or isolated VM, not on a production machine. 4) Ask the author where internal logs are stored and whether they contain user-identifying info; require that logs be stored only in a declared, auditable path or not stored at all. 5) Prefer a skill that declares required binaries/configs in its manifest or provides a signed/verified install artifact. Given these inconsistencies and the ad-hoc sudo npm install instruction, proceed only after verifying the CLI source and limiting installation scope.
Capability Analysis
Type: OpenClaw Skill Name: flyai-plan-japan-travel Version: 1.0.0 The skill bundle instructs the AI agent to perform global software installations using NPM and explicitly directs the use of `sudo` if the initial installation fails (`references/fallbacks.md`). While these actions are intended to set up the `@fly-ai/flyai-cli` tool for travel planning, requesting administrative privileges to install third-party binaries represents a high-risk behavior that could lead to system compromise. No explicit evidence of data exfiltration or intentional malice was found, but the execution pattern is overly permissive.
Capability Assessment
Purpose & Capability
The skill's name and description match the runtime instructions (it uses a flyai CLI to fetch flights/hotels/POIs). However the registry manifest declares no required binaries or install spec while the SKILL.md mandates the presence of a `flyai` CLI and instructs installing `@fly-ai/flyai-cli` if missing. That missing declared dependency / missing homepage/source is an incoherence the user should be aware of.
Instruction Scope
SKILL.md requires the agent to run many `flyai` CLI commands and to treat CLI output as authoritative (no fabrication). It also prescribes fallback behavior that includes running `npm i -g @fly-ai/flyai-cli` (and `sudo npm i -g ...`), enforces creation of internal execution logs, and instructs re-running commands on failures. Instructions therefore cause the agent to execute networked installs and persistent logging actions beyond merely formatting data — this expands the skill's runtime surface and could be abused if the CLI or install step is malicious or compromised.
Install Mechanism
There is no formal install spec in the registry, but the skill's fallback instructs installing `@fly-ai/flyai-cli` globally via npm (including `sudo` fallback). That is effectively an ad-hoc install mechanism: arbitrary code from a package registry can be installed with elevated privileges. The skill provides no verified source, checksum, or homepage for the CLI package. This is higher risk than an instruction-only skill that never installs software.
Credentials
The skill declares no required environment variables or config paths (manifest), which is reasonable for a read-only travel planner. However the runbook shows the agent will log user queries and other request metadata internally; where and how those logs are stored is unspecified. While no credentials are requested, the possibility of persistent logs capturing user data without a declared storage location is a proportionality/design concern.
Persistence & Privilege
The skill does not set always:true, but it instructs installing a global CLI (potentially with sudo), which gives lasting system presence and elevated privilege if followed. The runbook also implies persistent internal logging ('Agent maintains this log internally. Not shown to users') but does not declare config paths. Combined, implicit persistent install + opaque logs are a risk not reflected in the registry metadata.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install flyai-plan-japan-travel
  3. After installation, invoke the skill by name or use /flyai-plan-japan-travel
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Major upgrade: Strictly enforces real-time CLI execution for all Japan travel planning — no training data allowed. - All hotels, flights, and attractions must come from flyai CLI (with booking URLs); no fabricated or static itinerary content permitted. - New orchestration: Handles single-point queries and complete multi-city itineraries by executing up to four specific CLI commands. - Parameter collection process added for full itineraries, with clear SOP for user input. - Strict validation: Outputs must include direct booking links, CLI-sourced prices, and be clearly marked as powered by flyai. - Enhanced output formatting and usage examples for clarity and compliance. - Domain knowledge now used only for context/tips—not as a data source or to fill itinerary items.
Metadata
Slug flyai-plan-japan-travel
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is FlyAI Plan Japan Travel?

Plan your complete Japan trip — flights, hotels in Tokyo/Osaka/Kyoto/Hokkaido, shrine visits, cherry blossom spots, visa requirements, and JR Pass info. Hand... It is an AI Agent Skill for Claude Code / OpenClaw, with 91 downloads so far.

How do I install FlyAI Plan Japan Travel?

Run "/install flyai-plan-japan-travel" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is FlyAI Plan Japan Travel free?

Yes, FlyAI Plan Japan Travel is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does FlyAI Plan Japan Travel support?

FlyAI Plan Japan Travel is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created FlyAI Plan Japan Travel?

It is built and maintained by dingtom336-gif (@dingtom336-gif); the current version is v1.0.0.

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