Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Developer Tools
Our world in data
searches, retrieves, and summarizes content from Our World in Data using the `owid-catalog` Python module. Developed under Ubuntu. The developer would apprec...
skill openclawclawhub Free
searches, retrieves, and summarizes content from Our World in Data using the `owid-catalog` Python module. Developed under Ubuntu. The developer would apprec...
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0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.MD
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 0.1.3
Provenance
- Publisher
- rachmann-alexander
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
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.
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs
- SKILL.MD