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Forensic Data Engineer

Checked
daffy0208·vlatest·data·MIT

Analyzes complex datasets to reconstruct events, identify anomalies, and uncover hidden patterns for investigative purposes.

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 daffy0208/ai-dev-standards --skill forensic-data-engineer -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

daffy0208

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 daffy0208/ai-dev-standards at 32c3241e48.

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

Commit
32c3241e48
Manifest
skills/forensic-data-engineer/SKILL.md
Scanned
2 files, 1,214 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 forensic-data-engineer skill enables AI agents to perform deep-dive investigations on complex datasets, identifying anomalies, tracing data lineage, and generating comprehensive audit trails for compliance or security reviews. It acts as a specialized auditor within the data pipeline, ensuring integrity and transparency in how information is processed and stored.

When to use it

  • Investigating potential data breaches by tracing unauthorized access patterns across logs and databases.
  • Auditing financial transactions to detect irregularities or non-compliance with regulatory standards.
  • Analyzing system performance metrics to pinpoint root causes of recurring outages or bottlenecks.
  • Validating the accuracy of machine learning training sets by identifying bias or contamination sources.

Key capabilities

  • Automated anomaly detection within large-scale datasets.
  • Generation of immutable audit logs for every data operation.
  • Visualization of complex data relationships and lineage graphs.
  • Cross-referencing disparate data sources to build a complete forensic picture.

Example prompts

  • "Analyze the last 48 hours of server access logs to identify any suspicious IP addresses or unusual query patterns."
  • "Generate a full audit trail for all user account modifications made by the 'admin_01' role this week."
  • "Cross-reference sales data with inventory logs to find discrepancies that exceed a 5% variance threshold."

Tips & gotchas

Ensure your AI agent has read-only access permissions to sensitive forensic data sources to prevent accidental modification during analysis. For highly regulated industries, verify that the generated audit logs meet specific jurisdictional retention and formatting requirements before deployment.