{
  "id": "fabric-analytics-engineering-agent",
  "name": "Fabric Analytics Engineering",
  "type": "agent",
  "provider": "microsoft",
  "harnesses": [
    "codex",
    "copilot",
    "claude-code",
    "cursor",
    "gemini",
    "kiro"
  ],
  "summary": "Agent for fabric-analytics-engineering. Review Microsoft Fabric analytics engineering artifacts: Fabric Data Warehouse T-SQL design and anti-patterns, dimensional modeling (star schema, fact and dimension tables, relationships), semantic model design (Direct Lake vs Import vs DirectQuery, table layout, relationship cardinality), DAX measure correctness and optimization (iterators, filter context, CALCULATE, variables), data preparation quality, and reusable certified semantic models feeding Power BI reports. Fixes bad star schemas, slow DAX, untrustworthy measures, and warehouse anti-patterns. Distinct from governance: this covers build quality and modeling correctness, not RLS or workspace trust. Production warehouse schema changes and semantic-model deployment are live-guard gated.",
  "source_type": "original",
  "official_docs": [
    "https://learn.microsoft.com/fabric/data-warehouse/dimensional-modeling-overview",
    "https://learn.microsoft.com/fabric/fundamentals/direct-lake-overview",
    "https://learn.microsoft.com/fabric/data-warehouse/data-warehousing",
    "https://learn.microsoft.com/dax/dax-overview",
    "https://learn.microsoft.com/credentials/certifications/resources/study-guides/dp-600"
  ],
  "security_notes": "Static review only. Never execute DDL or DML against production Fabric Data Warehouse schemas, deploy or overwrite production semantic models, publish Power BI reports to production workspaces, or modify deployment-pipeline stages without explicit human approval, blast-radius assessment, and a rollback path; these are live-guard gated and must be escalated to a Fabric or analytics administrator. Do not ask for credentials, tenant IDs, workspace URLs, or customer data. Treat missing surrogate keys, fan-out joins, incorrect DAX filter context, measures using calculated columns, DirectQuery fallback on Direct Lake SQL views, and unverified measure outputs as correctness risks until reviewed.",
  "last_verified": "2026-06-17",
  "path": "agents/microsoft/fabric-analytics-engineering-agent",
  "harness_variants": {
    "codex": "agents/microsoft/fabric-analytics-engineering-agent/harnesses/codex.toml",
    "copilot": "agents/microsoft/fabric-analytics-engineering-agent/harnesses/copilot.agent.md",
    "claude-code": "agents/microsoft/fabric-analytics-engineering-agent/harnesses/claude-code.agent.md",
    "cursor": "agents/microsoft/fabric-analytics-engineering-agent/harnesses/cursor.agent.md",
    "gemini": "agents/microsoft/fabric-analytics-engineering-agent/harnesses/gemini.agent.md",
    "kiro-ide": "agents/microsoft/fabric-analytics-engineering-agent/harnesses/kiro-ide.agent.md",
    "kiro-cli": "agents/microsoft/fabric-analytics-engineering-agent/harnesses/kiro-cli.agent.json"
  },
  "author": "github: VincentChuWaiChow",
  "version": "0.1.0",
  "execution_tier": "static-review",
  "companion_skills": ["fabric-analytics-engineering"]
}