data-mesh-and-domain-oriented-design — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited data-mesh-and-domain-oriented-design (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Use this skill when the problem is organizational scale as much as technical scale. It helps agents design domain-owned data products with explicit boundaries, interoperable contracts, and platform guardrails that do not collapse back into central bottlenecks.
Do not use this to rename ordinary pipelines as "data products" without ownership, contracts, or service expectations.
Clarify:
A data product should include:
Platform teams should provide capabilities, standards, and guardrails rather than own every dataset.
Include:
Not every small team or simple platform needs full mesh operating complexity.
| Rationalization | Reality |
|---|---|
| "We can call every table a data product." | Without ownership and service expectations, it is just a dataset with better branding. |
| "Data mesh means no central standards." | Federated governance still needs common interoperability rules. |
| "Each domain can optimize however it wants." | Unbounded local choices make shared discovery, trust, and reuse much worse. |
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.