data-data-mesh

data-data-mesh is a skill for Claude Code, Codex from j4flmao/agent-skills. It costs 116 tokens per session (5,645 once invoked), scanned A, original, MIT.

A guide to data mesh, an organizational and technical approach where business domains own their data products while shared platform teams provide common tools and federated governance. A data product is a maintained dataset designed for other teams to use.

In plain words
What is it for?
It is for dividing ownership into domains, designing data products and their interfaces, planning self-service platform capabilities, and defining cross-domain sharing and governance.
Why use it?
It helps organizations avoid one central data team becoming the bottleneck, while keeping shared rules for quality, security, and access.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Codex.

Good fit It is for dividing ownership into domains, designing data products and their interfaces, planning self-service platform capabilities, and defining cross-domain sharing and governance.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/j4flmao/agent-skills/data-mesh
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add j4flmao/agent-skills --skill data-mesh
Clone the repo
git clone --depth 1 https://github.com/j4flmao/agent-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for data-data-mesh

README.md
[![agentmods](https://agentmods.dev/badge/skills/j4flmao/agent-skills/data-mesh/github.svg)](https://agentmods.dev/skills/j4flmao/agent-skills/data-mesh)
Your own site
<a href="https://agentmods.dev/skills/j4flmao/agent-skills/data-mesh"><img src="https://agentmods.dev/badge/skills/j4flmao/agent-skills/data-mesh/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for data-data-mesh

Your own site · 80×15
<a href="https://agentmods.dev/skills/j4flmao/agent-skills/data-mesh"><img src="https://agentmods.dev/badge/skills/j4flmao/agent-skills/data-mesh.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 116 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,645 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Data Exfiltration · line 152
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00116 $0.05645
Opus 5 $0.00058 $0.02823
Sonnet 5 $0.00023 $0.01129
Haiku 4.5 $0.00012 $0.00564

Measured 8d ago against content hash b2a0fe45a36e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

data-data-mesh scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/data/data-mesh/SKILL.md · 524 lines

How it starts

The opening of the file, as written. The whole thing — 524 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Data Data Mesh

Purpose

Design data mesh architecture with domain-owned data products, self-serve platform capabilities, and federated governance — enabling decentralized data ownership at scale.

Agent Protocol

Trigger

Exact user phrases: "data mesh", "data product", "domain ownership", "self-serve data platform", "federated governance", "data as a product", "compute plane", "data topology", "domain decomposition", "cross-domain data sharing".

Input Context

  • Organizational domains and team topology
  • Current data platform maturity
  • Data sharing patterns and pain points
  • Governance and compliance requirements
  • Number of data producers and consumers
  • Technology stack and cloud providers

Output Artifact

Data mesh architecture with domain boundaries, data product designs (input/output ports), platform capability map, cross-domain data sharing model, and federated governance framework.

Response Format

# Domain decomposition map
# Data product blueprint (ports, schema, SLA)
# Platform capability matrix
# Cross-domain sharing model
# Governance policies

No preamble. No postamble. No explanations. No filler/hedging/transitions. Compress output — why use many token when few do trick.

Completion Criteria

  • Domain decomposition aligned with business capabilities
  • Data product definition with input/output ports, schema, and SLA
  • Self-serve platform capabilities mapped to infrastructure
  • Cross-domain data sharing with discovery and access control
  • Federated governance model with global + local policies
  • Data mesh maturity assessment with improvement roadmap

Max Response Length

350 lines of configuration.

Workflow

Step 1: Decompose by Domain

Domain Business Capability Data Products
Commerce Order management, product catalog, cart orders, products, carts
Finance Revenue, billing, invoicing revenue, invoices, payments
Marketing Campaigns, attribution, leads campaigns, attribution, leads
Operations Inventory, fulfillment, logistics inventory, shipments, suppliers
Customer Profiles, segmentation, engagement customer_360, segments, interactions

Read the full file on GitHub · 524 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 524 lines · 116 tokens per session scan A b2a0fe45a36e

Subscribe to this mod's changes

data-data-mesh is a skill published in the GitHub repository j4flmao/agent-skills (23 stars, last pushed 6d ago), licensed MIT. It adds 116 tokens to every session and 5,645 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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