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Update Dataset

Listed
owid·vlatest·data·MIT

This skill updates datasets with new information, ensuring your data remains current and reliable for analysis and insights.

Repository

Install on your platform

This skill no longer installs under the name update-dataset. SKILL.md is marked internal, so the skills CLI hides it.

We check each listing against its upstream repository with the rules the skills CLI uses, last on 2026-10-22. We don't show a command we know will fail.

Repository install instructions

What we know about this skill

Publisher

owid

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 1 host that is neither well-known infrastructure nor declared in the skill's frontmatter: catalog.ourworldindata.org.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

    Hosts contacted

    catalog.ourworldindata.orgundeclared

    What it found

    • .claude/skills/update-dataset/SKILL.md:1008contacts catalog.ourworldindata.org
      curl -sL -O "https://catalog.ourworldindata.org/grapher/<ns>/<old_v>/<short>/$f"; done

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned owid/etl at 6173f8e9ff.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
6173f8e9ff
Manifest
.claude/skills/update-dataset/SKILL.md
Scanned
1 file, 1,042 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

The update-dataset skill enables AI agents to refresh and synchronize data within existing datasets, ensuring information remains current without requiring full rebuilds. It specifically targets the maintenance of tabular or structured data sources by applying incremental changes or re-fetching specific fields from connected APIs.

When to use it

  • Correcting outdated statistics in a report after new official figures are released.
  • Refreshing user lists or inventory counts that change frequently but don't need complete reconstruction.
  • Updating financial metrics in a dashboard where only the latest quarter's data has changed.
  • Synchronizing contact details from an external CRM to keep a local database accurate.

Key capabilities

  • Incremental updates to existing dataset records rather than full overwrites.
  • Integration with OWID ETL pipelines for structured data management.
  • Field-specific refreshing to minimize processing overhead on large datasets.

Example prompts

  • "Update the GDP figures in my 'Global_Economy_2024' dataset with the latest World Bank numbers."
  • "Refresh the user contact details in the 'Active_Subscribers' table by pulling from our marketing API."
  • "Incrementally update the inventory levels for items where stock has changed since yesterday's backup."

Tips & gotchas

Ensure your dataset schema matches the source data structure before initiating an update to prevent field mapping errors. This skill is designed for maintenance tasks; use full dataset regeneration if structural changes or massive data migrations are required instead.