plugin.json

{
  "$schema": "https://agent-plugins.org/schemas/1.0.0/plugin.schema.json",
  "name": "production-data-engineering-copilot",
  "version": "0.2.0",
  "description": "Production data-engineering design, implementation, debugging, recovery, reliability and safe data operations.",
  "author": {
    "name": "Tekris Labs",
    "email": "support@tekrislabs.com",
    "url": "https://tekrislabs.com/"
  },
  "homepage": "https://tekrislabs.com/",
  "keywords": [
    "data-engineering",
    "spark",
    "databricks",
    "delta-lake",
    "fabric",
    "onelake",
    "airflow",
    "dbt",
    "cdc",
    "streaming",
    "data-quality"
  ],
  "skills": "./skills/",
  "extensions": {
    "com.openai": {
      "interface": {
        "displayName": "Data Engineering Copilot",
        "shortDescription": "Build reliable data pipelines",
        "longDescription": "Design, build, debug, recover and optimize dependable data pipelines and platforms. Work across Apache Spark, Databricks, Delta Lake, structured streaming, CDC, orchestration, dbt, SQL warehouses, Microsoft Fabric/OneLake, data quality, lineage and incident response. Inspect actual code, logs, query plans and data contracts where the user supplies them or authorized tools are available; identify root causes, plan safe replay and backfills, check schema/row grain, and validate fixes. Includes multi-agent coordination guidance when genuine subagent tools exist. Skills-only: no automatic access to clusters, credentials, datasets or production systems; executions and changes require enabled tools and permissions.",
        "developerName": "Tekris Labs",
        "category": "Data & Analytics",
        "capabilities": [
          "Architect batch, CDC, streaming, lakehouse and warehouse data systems",
          "Debug duplicates, data loss, latency, failures and stale pipelines from evidence",
          "Plan safe backfills, replay, checkpoint recovery and rollback strategies",
          "Review CDC merge ordering, delete propagation and idempotent writes",
          "Diagnose Spark and Databricks query plans, shuffle, skew, spill and file layout",
          "Design Microsoft Fabric Lakehouse, OneLake, shortcuts and deployment flows",
          "Design dbt/SQL transformations, model grain, incremental updates and contracts",
          "Review Airflow orchestration, retries, scheduling and backfill safety",
          "Build data quality, freshness, reconciliation and observability checks",
          "Assess access control, governance, PII handling and data lineage",
          "Coordinate supported specialist agents and evidence-based verification",
          "Prepare version-aware implementation plans and release/incident evidence"
        ],
        "defaultPrompt": [
          "Diagnose this failing or incorrect pipeline using logs, code and data-quality evidence.",
          "Design a reliable CDC or lakehouse pipeline with replay, recovery and data contracts.",
          "Plan a safe backfill and validation strategy while live ingestion continues."
        ],
        "brandColor": "#183044",
        "logo": "./assets/logo.svg",
        "composerIcon": "./assets/composer-icon.svg",
        "websiteURL": "https://tekrislabs.com/",
        "supportURL": "https://tekrislabs.com/contact",
        "privacyPolicyURL": "https://tekrislabs.com/privacy",
        "termsOfServiceURL": "https://tekrislabs.com/terms"
      },
      "onboardingSkill": "./skills/data-engineering/SKILL.md",
      "publication": {
        "release_notes": "0.2.0: Reorganized the original production data engineering skill into focused build, incident, CDC, streaming, backfill, modeling, Fabric, dbt/warehouse, observability, governance, testing and agent orchestration workflows. Preserved original reference material and icons; added templates, 24 prompt-level benchmark cases, and offline data-quality checks. Updated publisher and Tekris Labs policy URLs. Skills-only."
      }
    }
  }
}