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Api Data Fetcher

Checked
meleantonio·vlatest·backend

Helps with API, data as part of agent workflows workflows.

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 meleantonio/awesome-econ-ai-stuff --skill api-data-fetcher -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

meleantonio

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 meleantonio/awesome-econ-ai-stuff at dd890d51c7.

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

Commit
dd890d51c7
Manifest
_skills/data/api-data-fetcher/SKILL.md
Scanned
2 files, 708 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

What it does

This skill assists economists and researchers in retrieving macroeconomic data from various APIs, including FRED (Federal Reserve Economic Data), World Bank, IMF, BLS, and OECD. It automatically generates clean, documented Python code to fetch this data, incorporating error handling and best practices for API usage. The generated code handles API key management using environment variables and provides basic data cleaning and formatting.

When to use it

  • Downloading macroeconomic indicators like GDP, unemployment rates, or inflation figures.
  • Creating custom datasets by combining data from multiple sources.
  • Automating regular updates of existing economic datasets for ongoing projects.
  • Fetching cross-country panel data for comparative analysis.
  • Retrieving financial data using the Yahoo Finance API.

Key capabilities

  • Data fetching from FRED, World Bank, IMF, BLS, OECD and Yahoo Finance APIs.
  • Automatic generation of Python code with error handling.
  • API key management through environment variables (e.g., FRED_API_KEY).
  • Data cleaning and formatting within the generated code.
  • Documentation of series definitions in the generated code.

Example prompts

  • "Fetch GDP and unemployment data from FRED for the years 2010 to 2023."
  • "Get World Bank data on poverty rates for India between 2015 and 2020."
  • “Can you generate code to pull inflation data from the BLS?”

Tips & gotchas

  • You'll need Python installed, along with the necessary API packages (e.g., fredapi, wbdata). The generated code will include installation instructions if a package is missing.
  • Ensure you have obtained and configured an API key for services like FRED; this often involves setting an environment variable (FRED_API_KEY).
  • The skill focuses on generating code—you'll need to execute the generated Python script to actually retrieve the data.