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Data Enrichment

Checked
merit-systems·vlatest·data

Automatically expands datasets with relevant external information to improve analysis and decision-making accuracy.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add merit-systems/x402scan-skills --skill data-enrichment -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

merit-systems

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 passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • 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 undeclared network calls: passed

    Makes no network calls.

    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.

  • 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 merit-systems/x402scan-skills at fcb4d82bc6.

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

Commit
fcb4d82bc6
Manifest
skills/data-enrichment/SKILL.md
Scanned
2 files, 279 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

data-enrichment

What it does

This skill enables AI agents to access and integrate external data sources to enhance their responses with up-to-date information. It allows agents to retrieve specific datasets, perform lookups, and combine raw inputs with contextual details from the internet or specialized databases.

When to use it

  • Providing current stock prices or market trends in financial analysis tasks.
  • Fetching real-time weather conditions for travel planning applications.
  • Retrieving latest news articles to summarize breaking events accurately.
  • Accessing public records or directory information for verification purposes.

Key capabilities

  • Connects to various external APIs and data endpoints.
  • Performs targeted searches across multiple data repositories.
  • Formats retrieved information into structured responses.
  • Validates data freshness before presenting insights.

Example prompts

  • "What are the latest earnings reports for tech companies this quarter?"
  • "Find current traffic conditions on I-95 between Boston and New York."
  • "Summarize recent developments in renewable energy policy from the last month."

Tips & gotchas

Ensure your AI agent has proper API keys configured, as many data sources require authentication. Be mindful of rate limits imposed by external providers to avoid service interruptions during high-volume queries.