semantic-trust 0.1.2

Score and certify dbt Semantic Layer models — trust bands, gates, and dbt-parse certification.

semantic-trust

Certify that dbt Semantic Layer models are safe to promote — a deterministic trust score, LLM-judged quality, and a dbt parse compile check. Not another way to write YAML.

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Why

dbt-labs' agent skills author semantic models — they scaffold YAML, wire measures, and generate metric definitions. semantic-trust picks up where authoring stops: it scores and certifies those models before they reach production.

Scoring runs five deterministic gates:

• Structural — required fields present, types correct, no dangling references.
• Uniqueness — no duplicate metric or dimension names across the project.
• Joinability — join paths resolve; foreign-key references match declared entities.
• Ownership — every model has an approved owner email (optionally domain-restricted).
• Completeness — descriptions, labels, and metric intent fields are populated.

On top of the gate results, an LLM-judgment pass evaluates description quality, naming clarity, and metric intent. The combined score maps to an A–F trust band. A model that clears all gates and passes LLM review earns an A; structural failures floor the score at F.

Certification adds a final compile check via dbt parse. A model that scores B or above and compiles cleanly is marked certified and safe to promote.

semantic-trust works on top of any dbt project — it reads the compiled semantic_manifest.json that dbt parse emits and requires no changes to your dbt project structure.

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How it's different

vs mf validate-configs — MetricFlow's own validator pins dbt-core<1.12, so it structurally cannot validate the current (1.12+/Fusion) Semantic Layer spec. semantic-trust validates both the legacy and the current spec — today it is the only tool that checks 1.12+/Fusion semantic models at all.

vs dbt-project-evaluator / dbt-checkpoint — those lint your dbt project structure (naming, staging layers, tests-exist, docs-exist). semantic-trust certifies your Semantic Layer — metrics, entities, joinability, ownership, and description quality. Different object, different failure mode: complementary, not redundant.

vs dbt Fusion / dbt parse alone — the compiler tells you a model is valid. semantic-trust tells you it is trustworthy — the deterministic gates plus an LLM-judgment pass on description quality, naming clarity, and metric intent that no compiler performs.

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Install

Claude Code plugin

Add the marketplace and install the plugin:

claude plugin marketplace add rj1224/semantic-trust
claude plugin install semantic-trust@semantic-trust

The second command uses the format <plugin-name>@<marketplace-name> (here both are semantic-trust). You can also install via the /plugin menu inside a Claude Code session.

Once installed, the MCP server starts automatically — the plugin's .mcp.json launches it via uvx --from semantic-trust semantic-trust-mcp. No manual server step is needed.

MCP server (standalone)

If you need to run the MCP server outside of the plugin:

uvx --from semantic-trust semantic-trust-mcp

This starts the semantic-trust-mcp stdio server, exposing three tools: scaffold_semantic_model, score_semantic_model, and validate_semantic_model.

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Quickstart

With the plugin installed, open a Claude Code session in your dbt project directory, then:

Natural language:

validate my semantic model

Claude routes this to the validate-semantics skill, which compiles your project, runs all five gates, applies LLM judgment, and returns a trust report with gate results, score, trust band, and any blocking issues.

Slash command:

/semantic-trust:validate <model>    # full trust report for a specific model

Authoring is available via natural language — the document-semantics and build-dbt-model skills bootstrap a first-pass semantic model for a model that has none yet, as a ramp into validation. For production authoring, prefer dbt-labs' own Semantic Layer agent skills.

The trust report shows gate-by-gate pass/fail, the A–F band, and a recommendation (promote / fix-and-retry / escalate).

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dbt version support

semantic-trust supports both the legacy and the current dbt Semantic Layer spec:

dbt Core version	Spec form	Notes
1.6 – 1.11	Legacy — top-level semantic_models: block + standalone measures: in schema.yml	mf validate-configs available as an additional validation pass
1.12+ / Fusion	Latest — model-annotation form: semantic metadata lives inside models: blocks	mf validate-configs not supported (skipped automatically)

dbt parse is the universal compile gate for both versions — semantic-trust always runs it first. mf validate-configs is a legacy-only bonus pass and is skipped automatically on 1.12+ projects.

The spec version is detected from target/semantic_manifest.json at runtime (the compiled output of dbt parse); no configuration is required.

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Not affiliated with dbt Labs

semantic-trust references the dbt ecosystem and is designed to work alongside dbt projects. It is not an official dbt product and is not affiliated with, endorsed by, or supported by dbt Labs, Inc.

The vendored content under vendor/dbt-agent-skills/ consists of dbt-labs' public Semantic Layer spec guides, included under their Apache-2.0 license. See vendor/dbt-agent-skills/NOTICE for attribution and license terms. That content remains Apache-2.0; the rest of this project is MIT.

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Configuration

semantic-trust works with zero configuration. To enable the ownership gate's domain check, add a .semantic-trust.json file at your dbt project root:

{
  "approved_email_domains": ["example.com"]
}

With approved_email_domains set, the ownership gate fails any model whose owner.email does not match one of the listed domains. Without this config key, the ownership gate only checks that an email is present.

No other configuration keys are required or supported.

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License

This project is licensed under the MIT License — see the LICENSE file.

Vendored content under vendor/dbt-agent-skills/ is licensed under the Apache-2.0 License — see vendor/dbt-agent-skills/NOTICE and vendor/dbt-agent-skills/LICENSE.