> ## Documentation Index
> Fetch the complete documentation index at: https://docs.cognite.com/llms.txt
> Use this file to discover all available pages before exploring further.

> ## Agent Instructions
> Cognite Data Fusion (CDF) is an industrial DataOps platform. Prefer English docs unless the user asks for another locale.
> Follow /_llms/ index links recursively until you reach page URLs ending in .md. Fetch those Markdown twins instead of HTML.
> For REST APIs, default to calendar version 20230101 (stable). Use 20230101-beta or 20230101-alpha only if the user is on a preview API. Cite paths under /api-reference/concepts/<version>/ and the Cdf-Version header. Prefer the Python SDK (cognite-sdk) unless the user is in JavaScript/TypeScript.
> Start here by task: platform overview /cdf/index.md; data modeling /cdf/dm/index.md; data integration /cdf/integration/index.md; access /cdf/access/index.md; CDF Toolkit /cdf/deploy/cdf_toolkit/index.md; REST quickstart /dev/quickstart.md; Python SDK https://cognite-sdk-python.readthedocs-hosted.com/en/stable/; Atlas AI /cdf/atlas_ai/concepts/index.md; Flows apps /cdf/flows/index.md; MCP and IDE setup /dev/guides/ide_ai_integration.md.
> For implementation work, also load /skill.md.

# Metadata reference for Cognite documentation

> Required metadata fields for Cognite documentation articles, including title, description, content-type, audience, experience-level, lifecycle, and article-type.

Metadata in Cognite documentation articles enables localization, reporting, search discoverability, and site experience customization. Add metadata in the YAML frontmatter at the top of each Markdown file.

<Note>
  **Canonical source for agents:** Allowed values and validation rules live in `.agents/skills/content-metadata/SKILL.md` in this repository. This article is the human-readable reference; when the two differ, the skill is authoritative.
</Note>

<Note>
  Metadata values are case-sensitive.
</Note>

Every article must include all required fields. If you are editing an existing article, check that the required fields are present and correct.

## Example YAML frontmatter

```yaml wrap theme={"languages":{"custom":["/_languages/kuiper.json","../_languages/kuiper.json"]}}
---
title: How to write a fantastic article
description: Step-by-step guidance for planning, drafting, and publishing a Cognite documentation article that meets content standards.
content-type: procedure
article-type: article
audience: developer
experience-level: 200
lifecycle: use
---
```

## Required fields

Every article must include all of the following fields.

| Field | Value | Purpose |
| - | - | - |
| `title` | Max 80 character title | Used in site search, SEO, and to help AI provide precise answers. |
| `description` | 75–300 character summary | Used in site search, SEO, and to help AI provide precise answers. |
| `content-type` | See [Content type](#content-type) | Classifies the type of content in the article. |
| `audience` | See [Audience](#audience) | Defines the primary target audience for the article. |
| `experience-level` | See [Experience level](#experience-level) | Defines the expected experience level of the reader. |
| `lifecycle` | See [Lifecycle](#lifecycle) | Maps the article to a stage in the customer lifecycle. |
| `article-type` | See [Article type](#article-type) | Distinguishes standalone articles from landing pages. |

## Optional fields

| Field | Value | Purpose |
| - | - | - |
| `sidebarTitle` | Max 30 character title for the sidebar | Shorter label for the sidebar when the title is too long. |
| `to-L10N` | `true` | Includes the article in content localization/translation handoff packages. |

## Content metadata fields

The following fields are required in every article. They classify articles for reporting, search discoverability, and AI answer precision.

### Audience

The `audience` field defines the main target audience for the article.

Valid values for the `audience` field:

| Value | Description |
| - | - |
| `businessUser` | <p>Professional who leverages Cognite products to drive business outcomes and operational improvements.</p><p>Focuses on extracting insights from data to inform strategic decisions, optimize processes, and achieve organizational goals. Typically has domain expertise but may have limited technical background.</p> |
| `administrator` | <p>Technical professional responsible for the deployment, configuration, and ongoing management of Cognite environments.</p><p>Ensures system reliability, performance, and compliance while managing user access and maintaining security standards. Works closely with IT teams and manages both cloud and on-premises infrastructure.</p> |
| `dataEngineer` | <p>Technical expert who designs, builds, and maintains data pipelines and infrastructure within Cognite ecosystems.</p><p>Responsible for data ingestion, transformation, and quality assurance. Bridges the gap between raw data sources and analytics-ready datasets, ensuring scalable and reliable data solutions.</p> |
| `developer` | <p>Software professional who builds applications, integrations, and custom solutions using Cognite APIs and SDKs.</p><p>Creates user-facing applications, automates workflows, and extends platform capabilities. Has strong programming skills and focuses on delivering technical solutions that meet business requirements.</p> |
| `aiEngineer` | <p>Specialist focused on developing and deploying artificial intelligence and machine learning solutions using Cognite's AI capabilities.</p><p>Builds predictive models, implements knowledge mining solutions, and creates intelligent automation. Combines domain expertise with advanced analytics and AI/ML engineering skills.</p> |
| `appMaker` | <p>Citizen developer or business analyst who creates applications and automates processes using low-code/no-code tools and platforms.</p><p>Bridges business needs with technical solutions without extensive programming knowledge. Focuses on rapid prototyping and solving immediate business challenges through configuration-based development.</p> |
| `dataAnalyst` | <p>Professional who transforms raw data into actionable business insights using Cognite's analytics tools.</p><p>Creates reports, dashboards, and data models to support decision-making. Combines business acumen with analytical skills to identify trends, patterns, and opportunities for operational improvements.</p> |
| `dataScientist` | <p>Advanced analytics professional who applies statistical methods, machine learning, and domain expertise to solve complex business problems.</p><p>Conducts experiments, builds predictive models, and develops data-driven solutions using Cognite's data science capabilities. Focuses on research, hypothesis testing, and advanced analytics.</p> |
| `securityEngineer` | <p>Cybersecurity specialist responsible for implementing and maintaining security controls within Cognite environments.</p><p>Manages identity and access management, monitors threats, and ensures compliance with security policies. Balances security requirements with operational needs and user accessibility.</p> |
| `solutionArchitect` | <p>Strategic technical leader who designs comprehensive solutions that integrate Cognite products with existing enterprise systems.</p><p>Responsible for technical strategy, system integration patterns, and ensuring solutions meet both technical and business requirements. Provides guidance on best practices and implementation approaches.</p> |
| `internal` | <p>Cognite employee or internal stakeholder who requires access to proprietary information, internal processes, or company-specific documentation.</p><p>Content targeting this audience includes internal tools, procedures, and information not intended for external users.</p> |
| `partner` | <p>External organization or individual working in collaboration with Cognite, including system integrators, consultants, and technology partners.</p><p>Requires specialized knowledge about partnership programs, co-development opportunities, and integration requirements.</p> |
| `businessDecisionMaker` | <p>Executive or senior stakeholder responsible for strategic technology decisions and budget allocation.</p><p>Evaluates Cognite solutions from a business value perspective, focusing on ROI, competitive advantages, and organizational impact. May have limited technical background but strong business and industry expertise.</p> |

### Content type

The `content-type` field defines the type of content in the article. It matches the content types defined in the [content model](#).

Valid values for the `content-type` field:

| Value | Description |
| - | - |
| `concept` | Information that helps you **understand**. |
| `reference` | Information you **look up**. |
| `procedure` | Information that helps you **do**. |
| `tutorial` | Information that helps you **learn**. |
| `quickstart` | Information that helps you **get going**. |
| `troubleshooting` | Information that helps you **fix**. |
| `map` | Hub or landing page that **organizes** other articles (pair with `article-type: map`). |

### Article type

The `article-type` field defines the type of article, [map topic](#) or [article](#), and is used for reporting.

Valid values for the `article-type` field:

| Value | Description |
| - | - |
| `map` | Landing page for product/role/area/keyword. |
| `article` | Standalone article. |

### Experience level

We use the `experience-level` field to define the experience level we expect the reader of the article to have. It is used for reporting.

Valid values for the `experience-level` field:

| Value | Description |
| - | - |
| `100` | Beginner: Learn the fundamentals. |
| `200` | Intermediate: Build on your experience with in-depth skills. |
| `300` | Advanced: Learn about specialized topics. |

### Lifecycle

We use the `lifecycle` field to define which part of the customer lifecycle the article is intended for. It is used for reporting.

Valid values for the `lifecycle` field:

| Value | Description |
| - | - |
| `investigate` | Attract |
| `verify` | Convert |
| `setup` | Onboard |
| `use` | Engage |
| `support` | Support |
| `transform` | Transform |