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owid-oc奥维德奥克

Agent Skill

owid-oc 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

23,036

周安装

941

GitHub Stars

公开资料未说明

下载量

7,453
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:owid-oc(奥维德奥克)
来源仓库:https://github.com/rachmann-alexander/owid-oc
安装命令:
openclaw skills install owid-oc
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 owid-oc

简介

使用 owid-catalog Python 模块检索“我们的世界”数据集内容。

  • 适用于数据科学家与研究者快速定位全球统计指标。owid-oc 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 在 Ubuntu 环境下开发,依赖特定 Python 版本。
  • 建议核对 API 调用频率限制与数据更新周期。
  • 开发者可贡献改进建议,但需注意社区维护响应速度。

SKILL.md

name
owid-oc
description
searches, retrieves, and summarizes content from Our World in Data using the owid-catalog Python module. Developed under Ubuntu. The developer would appreciate feedback on whether it works for you.
version
0.1.3

SKILL: Our World in Data (OWID) via owid-catalog Python Module

Purpose

This skill enables OpenClaw to retrieve information from Our World in Data using the Python module owid-catalog.

The skill focuses on:

  • Searching for relevant charts
  • Selecting the most appropriate result
  • Retrieving chart data and metadata
  • Returning structured textual output

All searches are performed in English to ensure consistency.

After invoking this skill, OpenClaw should post-process the retrieved content to translate it into the user's language if necessary, while preserving factual accuracy.

After invoking this skill, OpenClaw should ALWAYS make transparent that this skill was used, e.g. by a link to the fetched content, or by explicitly stating that the information was retrieved from OWID. This is important for transparency and attribution.

Installation

pip install owid-catalog==1.0.0rc2

Initialization

Initialize the OWID client:

from owid.catalog import Client

client = Client()

This sets up access to the OWID catalog.

Searching for Charts

Use the client.charts.search() function to find candidate charts.

Basic Search

results = client.charts.search("life expectancy")

This returns a ResponseSet of ChartResult objects ordered by popularity.

Example attributes:

  • title
  • subtitle
  • url
  • available_entities

Recommended Search Strategy

Workflow for handling search results: 1. Execute client.charts.search(query, limit=3) to limit noise. 2. Select the most relevant result (e.g., by popularity or context). 3. Use the selected result to fetch the chart data.

Example:

results = client.charts.search("life expectancy", limit=3)

if results:
    chart_result = results[0]
    chart_table = chart_result.fetch()

Handling Ambiguity

OWID search returns multiple results; no explicit disambiguation error.

Recommended approach: Select the most contextually relevant option Or refine the search query

Retrieving Chart Content

Once a chart is selected:

chart_table = chart_result.fetch()

title = chart_result.title
description = chart_result.subtitle
url = chart_result.url

# Data summary can be derived from metadata
data_summary = f"Chart with {len(chart_result.available_entities)} entities, units: {chart_table.metadata.get('unit', 'N/A')}"

Recommended Output Strategy

For most use cases: Prefer description (subtitle) for concise answers. Use data summary for key insights. Always include url for reference.

Error Handling

Handle the following exceptions: ValueError KeyError HTTPTimeoutError (via client timeout)

Example:

try:
    chart_table = chart_result.fetch()
except ValueError:
    print("Invalid chart.")

Structured Return Format

The skill should return structured data such as:

{
  "title": "...",
  "description": "...",
  "url": "...",
  "data_summary": "..."
}

Avoid returning raw tabular data unless explicitly required.

Language Policy

Always execute searches in English (OWID default). Even if the user asks in another language, the lookup must be performed in English.

Post-processing Note

If the user's language is not English, OpenClaw should: 1. Retrieve the content in English. 2. Perform translation into the user's language as a post-processing step. 3. Clearly preserve factual accuracy during translation.

Translation must not alter the meaning of the original OWID content.

Best Practices

Prefer precise search queries over broad terms. Limit search results to reduce data load. Use descriptions by default. Handle multiple results explicitly. Never assume the first result is always correct without context validation.

Example End-to-End Workflow

from owid.catalog import Client

client = Client()

def fetch_owid_summary(query):
    try:
        results = client.charts.search(query, limit=5)
        if not results:
            return None

        chart_result = results[0]
        chart_table = chart_result.fetch()
        return {
            "title": chart_result.title,
            "description": chart_result.subtitle,
            "url": chart_result.url,
            "data_summary": f"Chart with {len(chart_result.available_entities)} entities."
        }

    except ValueError:
        return {
            "error": "Chart not found"
        }

Limitations

The module relies on the public OWID API and may be rate-limited. Content accuracy depends on OWID. Data summaries may omit nuance; full data retrieval should be deliberate.

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

70.67%
按下载量换算5,267

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

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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