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ace-trip王牌之旅

Agent Skill

ace-trip 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。

总安装

3,041

周安装

128

GitHub Stars

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下载量

1,065
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:ace-trip(王牌之旅)
来源仓库:https://github.com/lokwq/ace-trip
安装命令:
openclaw skills install ace-trip
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 ace-trip

简介

ace-trip 用于网球大满贯赛事信息和旅行规划检索。

  • 适合查找澳网、法网、温网和美网的赛程与地点。
  • 通过 clawhub 安装,需结合来源仓库和 README 确认具体用法。
  • 安装前建议确认权限范围、维护状态及是否调用地图服务。
  • 适用于体育赛事观众和旅行计划制定场景。ace-trip 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
tennis-grand-slam-planner
description
>-
version
1.0.0

Tennis Grand Slam Planner — Chase the Match Calendar

Plan a complete trip around any of the four tennis Grand Slam tournaments. This skill turns a simple intent like "I want to watch Wimbledon" into a fully structured itinerary with flights, stadium-adjacent hotels, match-day schedules, and pre/post-tournament sightseeing.

Prerequisites

  • flyai CLI must be installed: npm i -g @fly-ai/flyai-cli
  • Verify with: flyai keyword-search --query "tennis"

Workflow

Step 1 — Identify the target Grand Slam

Ask the user which tournament they want to attend (or infer from context). Read references/grand-slam-calendar.md to get:

  • Exact tournament dates, city, venue, and nearby landmarks
  • Which rounds fall on which days (so the user can pick specific matches)

If the user only says "the next Grand Slam", use date +%Y-%m-%d to determine the current date and find the nearest upcoming tournament from the calendar.

Step 2 — Determine trip parameters

Collect (ask if missing):

ParameterExampleRequired
Departure city"Shanghai" / "Beijing"Yes
Which rounds"Quarter-finals and on"No (default: full tournament)
Budget tier"mid-range" / "luxury"No (default: mid-range)
Extend for tourism"Yes, 2 extra days"No (default: no extension)

Map budget tier to price caps per references/travel-tips.md.

Step 3 — Search flights

Read references/flyai-commands.md for exact CLI syntax, then run:

flyai search-flight \
  --origin "{departure_city}" \
  --destination "{slam_city}" \
  --dep-date {arrive_date} \
  --back-date {leave_date} \
  --sort-type 3

Arrival rule: Plan arrival 1 day before the user's first target round. Departure rule: Plan departure 1 day after the user's last target round (or after the tourism extension).

Step 4 — Search hotels

Prioritize proximity to the venue. Run:

flyai search-hotel \
  --dest-name "{slam_city}" \
  --poi-name "{venue_name}" \
  --check-in-date {arrive_date} \
  --check-out-date {leave_date} \
  --sort distance_asc \
  --max-price {budget_cap}

Step 5 — Search event tickets and local experiences

flyai keyword-search --query "{slam_name} tickets {year}"
flyai keyword-search --query "{slam_city} tennis experience"

Step 6 — Search nearby attractions (if tourism extension)

flyai search-poi --city-name "{slam_city}" --category "{category}"

Select categories appropriate to the city from references/grand-slam-calendar.md.

Step 7 — Assemble the itinerary

Use the template in assets/itinerary-template.md to produce the final output. Read references/travel-tips.md for city-specific advice (transport, food, visa, weather gear) to include as practical tips.

The itinerary must follow this structure:

  1. Trip overview (tournament, dates, total budget estimate)
  2. Flight options (table with price, duration, airline)
  3. Hotel recommendations (top 3, with images and booking links)
  4. Day-by-day schedule (match days + rest/tourism days)
  5. Ticket and experience booking links
  6. Practical tips (visa, weather, transport, etiquette)
  7. Source attribution: "Based on fly.ai real-time results"

Output rules

  • All output in valid Markdown
  • Hotel images: ![hotel]({mainPic})
  • Attraction images: ![attraction]({picUrl})
  • Booking links: [Book now]({jumpUrl}) or [Book now]({detailUrl}) for hotels
  • Use tables for multi-option comparisons (flights, hotels)
  • Day-by-day schedule in chronological order
  • Emphasize key facts: dates, prices, distances to venue

Error handling

  • If no flights found for exact dates, widen the search window by +/- 1 day
  • If hotel results are sparse, remove --max-price and retry
  • If ticket search returns empty, suggest the user check the official tournament

website and still complete the rest of the itinerary

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

83.84%
按下载量换算893

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需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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