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Data Mesh Expert

Checked
personamanagmentlayer·vlatest·other·Apache-2.0

Analyzes data mesh architectures, identifies bottlenecks, and suggests improvements for decentralized data ownership.

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 personamanagmentlayer/pcl --skill data-mesh-expert -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

personamanagmentlayer

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 personamanagmentlayer/pcl at 79ccaa9820.

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

Commit
79ccaa9820
Manifest
stdlib/data/data-mesh-expert/SKILL.md
Scanned
2 files, 1,031 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 enables AI agents to analyze and design data mesh architectures, focusing on decentralized data ownership and a product-centric approach. It leverages deep knowledge of core data mesh principles like domain-oriented ownership, treating data as a product, self-serve infrastructure, and federated governance. The agent can help structure domains, define data products within those domains, and outline team compositions for effective data management.

When to use it

  • When designing a new data architecture that requires decentralized data ownership.
  • To identify bottlenecks or inefficiencies in an existing data mesh implementation.
  • For guidance on structuring domains and defining data products based on business context.
  • To understand the roles and responsibilities within a domain-oriented data team.

Key capabilities

  • Expertise in Data Mesh principles (Domain Ownership, Data as a Product, Self-Serve Infrastructure, Federated Governance).
  • Ability to define domain structures including bounded contexts and data products.
  • Knowledge of team composition for domains (product owner, data engineers, analytics engineers).
  • Understanding of Domain Data Product Architecture.

Example prompts

  • "Describe the ideal domain structure for a company with sales, marketing, product, and finance departments."
  • "What are some key considerations when defining 'data as a product' within the sales domain?"
  • "How would I implement federated computational governance in a data mesh environment?"

Tips & gotchas

  • The skill requires understanding of basic data architecture concepts.
  • It focuses on design and analysis, not implementation details of specific technologies.
  • To get the best results, provide clear context about your organizational structure and business goals.