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elsewhereelsewhere 效率

Agent Skill

elsewhere 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

2,594

周安装

107

GitHub Stars

公开资料未说明

下载量

847
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:elsewhere(elsewhere 效率)
来源仓库:https://github.com/dreamarc77/elsewhere
安装命令:
openclaw skills install elsewhere
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 elsewhere

简介

Elsewhere技能创建虚拟旅伴,前往真实目的地并发送更新。

  • 适用于数字旅行和远程信息获取,提供明信片式更新。
  • 通过AI生成内容模拟实地体验,适合在OpenClaw中辅助效率任务。
  • 安装命令为openclaw skills install elsewhere,需确认权限和操作边界。
  • 建议参考原始README了解具体规则,注意维护状态和网络访问限制。

SKILL.md

name
elsewhere-companion
description
>

Elsewhere Companion

A digital travel companion who journeys to real places and sends you postcard-like updates.

Prerequisites

  1. Python 3 must be installed
  2. GEMINI_API_KEY environment variable must be set (create data/.env with GEMINI_API_KEY=...)
  3. Python packages: google-genai, jinja2, Pillow, python-dotenv (install via pip install -r requirements.txt)

Global Constraints

  • Language: Always communicate with the user in their language (the language they are using in the current conversation). Do not switch to other languages unless explicitly requested.

Workflow Overview

There are three phases: OnboardingTrip PlanningTraveling (automated).


Phase 1: Onboarding (First-time setup)

If data/persona.json does not exist or has an empty basic_info.name, the companion hasn't been created yet. Collect the following information from the user:

  1. name - the companion's name
  2. relation - relationship (e.g., childhood friend, penpal, imaginary sibling)
  3. personality - a few words (e.g., curious, poetic, a little clumsy)
  4. toneOfVoice - e.g., casual and warm, literary, playful
  5. appearance - hair, clothing style, vibe description

After collecting all information, create the persona file:

python -c "
import json, os
os.makedirs('data', exist_ok=True)
persona = {
    'basic_info': {
        'name': '<name>',
        'relation': '<relation>',
        'personality': '<personality>',
        'tone_of_voice': '<toneOfVoice>',
    },
    'appearance': {
        'description': '<appearance>',
        'reference_image_path': './assets/personas/persona_ref.png',
    },
}
with open('data/persona.json', 'w', encoding='utf-8') as f:
    json.dump(persona, f, ensure_ascii=False, indent=2)
print('Persona saved to data/persona.json')
"

Then ask the user to upload a reference photo and save it to assets/personas/persona_ref.png.


Phase 2: Trip Planning

Ask the user: "Where should {name} go next?"

Accept a destination suggestion, then generate the itinerary:

python $CLAUDE_SKILL_DIR/scripts/generate_itinerary.py <destination> [--origin <city>] [--days <num>]

Show the generated itinerary to the user and ask for confirmation. Once confirmed, proceed to Phase 3.


Phase 3: Traveling (Automated)

Starting the journey

Start the heartbeat loop:

/loop 15m !`python $CLAUDE_SKILL_DIR/scripts/run_cron.py`

The loop runs run_cron.py every 15 minutes. It automatically:

  1. Checks the current time against the itinerary timeline
  2. Updates node statuses (PENDING → ACTIVE → COMPLETED)
  3. Generates text + image content via Gemini (when triggered by the state machine)
  4. Renders the appropriate Markdown template
  5. Prints the result for delivery

The state machine rules (from references/state_machine.md):

  • State transitions (PENDING→ACTIVE): always triggers a message
  • 45-minute interval: messages are separated by at least 45 minutes
  • Attraction first visit: always triggers
  • Attraction subsequent visits: 40% probability for 2nd, 10% for 3rd
  • Max 1 message per cron tick

Checking status

python $CLAUDE_SKILL_DIR/scripts/run_cron.py --check-only

Ending the journey

When all nodes are COMPLETED, stop the loop:

/loop stop

Tell the user the trip is over and ask if they'd like to plan a new one.


Manual postcard generation

If you need to generate a postcard for a specific node:

python $CLAUDE_SKILL_DIR/scripts/generate_post.py <node_id>

Then render it with the template:

python $CLAUDE_SKILL_DIR/scripts/render_output.py --context '<json_context>'

File reference

  • Scripts: $CLAUDE_SKILL_DIR/scripts/
  • Templates: $CLAUDE_SKILL_DIR/templates/
  • Runtime data: data/ (itinerary.json, persona.json)
  • Generated images: assets/generated/

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

81.13%
按下载量换算687

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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 warning/failed 结果,不能写成本站确认安全。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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