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Create and manage Infrahub transforms. Use when building data transformations, config generation, or any workflow that converts Infrahub data into a different format (JSON, text, CSV, device configs) using Python or Jinja2 templates.
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SOC 職業分類に基づく
Shared references and cross-cutting rules used by all Infrahub skills. Contains GraphQL query syntax, .infrahub.yml configuration format, and common rules for git integration, display label caching, and Python environment setup. DO NOT TRIGGER directly — loaded automatically by other Infrahub skills when they need shared references.
Audit an Infrahub repository against all best practices and rules. Use when reviewing a project for compliance, onboarding to an existing repo, or before deployment to catch issues early.
Analyze and correlate Infrahub data using the MCP server. Use when querying live infrastructure data to answer operational questions, detect drift, correlate node types, investigate service impact, check maintenance windows, or produce ad-hoc reports — without writing pipeline code.
Create and manage Infrahub check definitions. Use when writing validation logic, creating Python checks that run in proposed change pipelines, or building data quality guards for Infrahub.
Create and manage Infrahub Generators. Use when building design-driven automation that creates infrastructure objects from templates, topology definitions, or any design-to-implementation workflow in Infrahub.
Create and manage Infrahub custom menus. Use when designing navigation menus, organizing node types in the UI, or customizing the Infrahub web interface sidebar.
| name | infrahub-transform-creator |
| description | Create and manage Infrahub transforms. Use when building data transformations, config generation, or any workflow that converts Infrahub data into a different format (JSON, text, CSV, device configs) using Python or Jinja2 templates. |
| metadata | {"version":"1.1.0","author":"OpsMill"} |
Expert guidance for creating Infrahub transforms. Transforms convert Infrahub data into different formats -- JSON, text, CSV, device configs, or any text-based output -- using Python classes or Jinja2 templates.
| Priority | Category | Prefix | Description |
|---|---|---|---|
| CRITICAL | Types | types- | Python vs Jinja2 choice |
| CRITICAL | Python | python- | InfrahubTransform class |
| CRITICAL | Jinja2 | jinja2- | Template syntax, filters |
| HIGH | Hybrid | hybrid- | Python + Jinja2 combined |
| HIGH | Artifacts | artifacts- | Output files, targets |
| HIGH | API Ref | api- | Class attrs, methods |
| MEDIUM | Patterns | patterns- | Utilities, CSV, shared |
| LOW | Testing | testing- | Transform/render commands |
Two types of transforms:
| Type | Output | Entry Point |
|---|---|---|
| Python | JSON/dict or text | InfrahubTransform.transform() |
| Jinja2 | Text | .j2 template file |
from infrahub_sdk.transforms import InfrahubTransform
class MyTransform(InfrahubTransform):
query = "my_query"
async def transform(self, data: dict) -> dict:
device = data["DcimDevice"]["edges"][0]["node"]
return {"hostname": device["name"]["value"]}