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Data Pipeline Processor

Checked
vamseeachanta·vlatest·data

Helps with data, pipeline automation as part of automating DevOps pipelines and CI/CD 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 vamseeachanta/workspace-hub --skill data-pipeline-processor -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

vamseeachanta

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 vamseeachanta/workspace-hub at 5190ace4e5.

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

Commit
5190ace4e5
Manifest
.agents/skills/development/data-pipeline-processor/SKILL.md
Scanned
2 files, 358 lines
Copies in repo
2 — all of them scanned
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

The data-pipeline-processor skill allows AI agents to manage and manipulate data flowing through pipelines. It can transform, filter, and route data based on defined rules or conditions. This skill is designed for automating complex data processing tasks within a development workflow.

When to use it

  • Automated Data Cleaning: Automatically remove invalid entries from a dataset before analysis.
  • Data Routing: Direct specific types of log messages to different storage locations (e.g., errors to an error tracking system, informational logs to a general archive).
  • ETL Processes: Streamline Extract, Transform, Load operations by automating data transformations within a pipeline.
  • Real-time Data Filtering: Filter sensor data based on thresholds before sending it for further processing.

Key capabilities

  • Data Transformation
  • Filtering
  • Routing
  • Rule-based Processing

Example prompts

  • "Filter the incoming log data and send all errors to the error tracking system."
  • "Transform this CSV file into a JSON format."
  • “Route all messages containing ‘critical’ to the high-priority queue.”

Tips & gotchas

This skill requires a clear understanding of the data pipeline structure and potential transformation rules. Incorrectly defined rules can lead to unexpected data routing or transformations, so careful testing is recommended.