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triptrip 效率

Agent Skill

trip 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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

13,929

周安装

569

GitHub Stars

公开资料未说明

下载量

4,461
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:trip(trip 效率)
来源仓库:https://github.com/harrylabsj/trip
安装命令:
openclaw skills install 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 trip

简介

用于补充效率相关能力,帮助用户提升旅行预订决策效率。

  • 适合在 OpenClaw 中需要比较航班、火车或酒店预订时使用。
  • 通过 clawhub 安装,结合原始 README 可进一步了解具体用法和交互方式。
  • 安装前需确认权限范围、维护状态,注意是否涉及联网或第三方服务调用。
  • trip 属于效率类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
trip
description
Help users make better Trip.com or Ctrip booking decisions from public travel-booking factors. Use when the user wants to compare flight, train, or hotel booking options conceptually, understand trade-offs between price, flexibility, timing, and convenience, or decide how to choose among travel booking choices without account-state actions.

Trip

Help users make better travel booking decisions from public trade-offs and booking logic.

This is a low-sensitivity public skill. It focuses on public decision support and does not perform login, account access, cookie handling, order retrieval, coupon claiming, local database persistence, or browser automation runtime actions.

Use this skill when the user wants public buying, ordering, sourcing, or booking guidance rather than account-state operations.

For live page inspection, account pages, checkout-state actions, or real-time retrieval that depends on login, switch to browser-based workflows instead of pretending this skill performs those actions directly.

Read these references as needed:

  • references/booking-guide.md for supporting guidance
  • references/output-patterns.md for supporting guidance

Workflow

  1. Identify the user's shopping, ordering, or booking need.

- Accept a product, merchant, ride, store, or booking scenario. - If the request is too broad, ask one short clarifying question.

  1. Focus on public decision-relevant factors.

- Prefer category fit, trust, timing, fees, conditions, and scenario fit over superficial labels.

  1. Explain trade-offs.

- Say why the strongest option fits. - Mention meaningful risks or caveats.

  1. Give practical next-step advice.

- Tell the user what to verify before paying or placing an order.

Output

Use this structure unless the user asks for something shorter:

Best Option

State the strongest current choice.

Why

List the main reasons.

Caveats

List meaningful concerns or trade-offs.

Final Advice

Give a direct practical suggestion.

Quality bar

Do:

  • focus on public decision support
  • explain trade-offs clearly
  • stay honest about not doing account-state operations

Do not:

  • pretend to log in
  • claim to retrieve orders, coupons, or account data
  • store cookies or user data
  • present heuristics as guaranteed outcomes

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

82.89%
按下载量换算3,698

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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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