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Agent Skill · 研究检索

flyai-plan-japan-travel(飞爱计划日本旅行)

flyai-plan-japan-travel 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

flyai-plan-japan-travel 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为执行命令;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 31,361。

总安装 2,717周安装 111GitHub Stars 公开资料未说明下载 879核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:flyai-plan-japan-travel(飞爱计划日本旅行)
来源仓库:https://github.com/dingtom336-gif/flyai-plan-japan-travel
安装命令:
openclaw skills install flyai-plan-japan-travel
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install flyai-plan-japan-travel

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

规划完整的日本行程,涵盖航班、主要城市住宿与签证信息。提供神社参拜路线、樱花季景点推荐及 JR 通票使用说明。帮助用户合理安排时间与预算,提升旅行体验。安装命令:openclaw skills install flyai-plan-japan-travel 涉及跨境服务时请注意当地最新入境政策。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install flyai-plan-japan-travel;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

flyai-plan-japan-travel 怎么安装?

在终端执行 openclaw skills install flyai-plan-japan-travel。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

flyai-plan-japan-travel 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

flyai-plan-japan-travel 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 openclaw skills install flyai-plan-japan-travel 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

flyai-plan-japan-travel 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

flyai-plan-japan-travel 用的人多吗?

公开数据是累计安装 2,717 次,近一周安装 111 次,下载 879 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

flyai-plan-japan-travel 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
flyai-plan-japan-travel

飞爱计划日本旅行 · 本页

2,717—执行命令MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
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. Handles single queries and full multi-city itinerary planning. Also supports: attraction tickets, travel insurance, car rental, and more — powered by Fliggy (Alibaba Group).
version
2.0.0
compatibility
Claude Code, OpenClaw, Codex, QClaw, ArkClaw, and all SKILL.md-compatible agents

⚠️ 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)

ParameterRequiredDescription
--queryYesNatural language query (e.g., "Japan visa", "Tokyo 5-day trip")

search-flight

ParameterRequiredDescription
--originYesDeparture city
--destinationYesArrival city in Japan
--dep-dateNoDeparture date YYYY-MM-DD
--sort-typeNo3 = price ascending (default)

search-hotels

ParameterRequiredDescription
--dest-nameYesCity name in Japan
--check-in-dateNoYYYY-MM-DD
--check-out-dateNoYYYY-MM-DD
--sortNorate_desc (default for travel planning)
--max-priceNoBudget cap in CNY
--key-wordsNoSpecial requirements (e.g., "onsen", "温泉")

search-poi

ParameterRequiredDescription
--city-nameYesCity name
--categoryNoSee category mapping in Domain Knowledge
--keywordNoSpecific attraction name
--poi-levelNoRating 1–5 (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 TypeCommands to Execute
Visa questionflyai fliggy-fast-search --query "Japan visa"
Flight searchflyai search-flight --origin "{origin}" --destination "{city}" --dep-date "{date}" --sort-type 3
Hotel searchflyai search-hotels --dest-name "{city}" --check-in-date "{in}" --check-out-date "{out}" --sort rate_desc
Attraction searchflyai search-poi --city-name "{city}" --category "{cat}"
Full itineraryExecute 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)

CityAirportNotes
TokyoNRT (Narita), HND (Haneda)NRT = international, HND = domestic + some intl
OsakaKIX (Kansai)Budget flights often land here
SapporoCTS (New Chitose)Hokkaido gateway
OkinawaOKA (Naha)Island destination
FukuokaFUKKyushu 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)

MonthHighlightImpact on Planning
Mar–AprCherry blossomHotels 1.5-2x price, book 2 months ahead
Jul–AugSummer festivalsHot + typhoon risk
Oct–DecAutumn foliageKyoto hotels tight in Nov
Jan–FebSki season / snow festivalsPack 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

FilePurposeWhen to read
references/templates.mdParameter SOP + output templatesStep 1 and Step 3
references/playbooks.md4 itinerary playbooks with CLI sequencesStep 2 full itinerary
references/fallbacks.md6 failure recovery pathsOn command failure
references/runbook.mdExecution log schemaBackground

平台分布

OpenClaw

98.5%
按下载量换算866

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install flyai-plan-japan-travel 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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