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

# FAQ

> Answers to common questions about the Learning Commons Platform, Knowledge Graph, and Evaluators — covering pricing, access, data coverage, and integration. Organized by product area. Intended for developers evaluating fit or working through early integration.

## General

<Accordion title="What tools does Learning Commons offer?">
  Sign in to our [Learning Commons Platform](https://platform.learningcommons.org/) ↗ to use our 2 edtech development tools:

  | Tool                                 | What it does                                                                                  | Use cases                                                                                                                                                                                                                      |
  | :----------------------------------- | :-------------------------------------------------------------------------------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
  | [Knowledge Graph](/knowledge-graph/) | Consolidates academic standards, curricula, and learning science in expert-annotated datasets | Identify how your AI-generated educational content supports specific academic standards; Follow meaningful learning progressions when planning instructions; Adapt content aligned to one state standard to other states, etc. |
  | [Evaluators](/evaluators/)           | Measures the quality of AI-generated educational content                                      | Optimize your product's AI-generated outputs; Select the right model for your task; etc.                                                                                                                                       |
</Accordion>

<Accordion title="Do I need to pay to use Learning Commons tools?">
  No. Creating a [Learning Commons Platform](https://platform.learningcommons.org/) ↗ account is free and gives you full access to Knowledge Graph and Evaluators. Most Knowledge Graph datasets and all Evaluators are openly licensed and free to use. A small number of gated Knowledge Graph datasets may require users to accept separate licensing terms and fees from the dataset publishers.
</Accordion>

<Accordion title="Do I have to use both Knowledge Graph and Evaluators?">
  No. Knowledge Graph and Evaluators serve different stages of an AI content generation pipeline and can be used independently.

  | Tool                                                                                                           | When to use                                                                                     | Description                                                                                                                            |
  | :------------------------------------------------------------------------------------------------------------- | :---------------------------------------------------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------- |
  | [**Knowledge Graph**](/knowledge-graph/understanding-knowledge-graph/introduction#when-to-use-knowledge-graph) | Before or during content generation — to ground your AI with structured, standards-aligned data | Input-side tool that gives your AI structured, standards-aligned data to work with                                                     |
  | [**Evaluators**](/evaluators/understanding-evaluators/introduction#when-to-use-evaluators)                     | After content generation — to score output against pedagogical criteria                         | Output-side tool that scores the content your AI produces against pedagogical criteria like grade-level appropriateness and vocabulary |

  With that said, many teams find value in integrating both tools – Knowledge Graph to ground content generation and Evaluators to verify the output.
</Accordion>

## Learning Commons Platform

<Accordion title="Why do I need a Learning Commons Platform account?">
  Your [Learning Commons
  Platform](https://platform.learningcommons.org/) ↗ account allows you to:

  * Demo our evaluators in the [Evaluators Playground](/evaluators/getting-started/quickstart#evaluators-playground) ↗
  * Explore our datasets using the [Knowledge Graph Explorer](https://platform.learningcommons.org/apps/knowledge-graph/explorer) ↗
  * [Generate API
    keys](/api-reference/platform-api/overview) ↗ to integrate Learning Commons
    tools into your project
</Accordion>

<Accordion title="Why do I need an organization associated with my Learning Commons Platform account?">
  The [Learning Commons
  Platform](https://platform.learningcommons.org) ↗ manages
  access to API keys, gated datasets, team collaboration, and permissions by organization.

  You will be prompted to create your organization when first signing in to your Learning Commons Platform account. Any
  API keys you create will be linked to that organization automatically.
</Accordion>

<Accordion title="My API keys are linked to the wrong organization. What can I do?">
  Unfortunately, API keys can't be transferred between organizations. You'll need to create new API keys in the correct organization and update your projects to use them.

  Your old API keys will continue to work until you manually delete them, so you can migrate at your own pace.
</Accordion>

## Knowledge Graph

<Accordion title="Why should our team integrate Knowledge Graph?">
  With our datasets, edtech developers can more reliably produce AI-generated educational content that:

  * Aligns to academic standards
  * Incorporates high-quality curricula
  * Is rooted in learning science
  * Can be translated across states

  Check out [some common use cases](/knowledge-graph/understanding-knowledge-graph/introduction#when-to-use-knowledge-graph) of Knowledge Graph before getting started.
</Accordion>

<Accordion title="Can I use Knowledge Graph with any LLM?">
  Yes. Knowledge Graph is LLM-agnostic — you can use it with OpenAI, Google, Anthropic, or any other provider.

  If you're building an agent-based workflow, the [MCP server](/knowledge-graph/using-knowledge-graph/mcp-server) makes it easy to connect Knowledge Graph data directly to tools like [Claude](/knowledge-graph/using-knowledge-graph/claude-connector) or Cursor without writing custom retrieval logic.
</Accordion>

<Accordion title="What Knowledge Graph datasets are available now for my region?">
  Knowledge Graph covers all 50 U.S. states, with availability varying by dataset and subject. We do not currently offer international coverage.

  | Dataset                                                                                         | Coverage                                                                                                                                                                                                            |
  | :---------------------------------------------------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
  | [Academic Standards](/knowledge-graph/graph-reference/academic-standards)                       | All U.S. states for Math, ELA, Science, and Social Studies, plus WIDA English Language Development Standards                                                                                                        |
  | [Learning Components](/knowledge-graph/graph-reference/learning-components)                     | **Math:** Common Core and 40+ state frameworks.<br />**ELA:** Common Core and select states, currently grades K–2.<br /><br />[Supported frameworks](/knowledge-graph/graph-reference/learning-components#overview) |
  | [Standards Crosswalks](/knowledge-graph/graph-reference/standards-crosswalks)                   | In U.S. states where Learning Components alignment exists                                                                                                                                                           |
  | [Learning Progressions](/knowledge-graph/graph-reference/learning-progressions)                 | All U.S. states for Math (uses Common Core State Standards)                                                                                                                                                         |
  | [Curriculum](/knowledge-graph/graph-reference/curriculum)                                       | Math                                                                                                                                                                                                                |
  | [Learner Variability Navigator](/knowledge-graph/graph-reference/learner-variability-navigator) | Learning science                                                                                                                                                                                                    |

  We are actively expanding coverage across states and subjects.

  See our [Roadmap](/knowledge-graph/understanding-knowledge-graph/roadmap) for what's in progress, or contact [support@learningcommons.org](mailto:support@learningcommons.org) ↗ if you need help finding data for your region.
</Accordion>

<Accordion title="Can I request a dataset or standard that isn't available yet?">
  Yes. We actively expand Knowledge Graph coverage based on demand.

  Check the [Roadmap](/knowledge-graph/understanding-knowledge-graph/roadmap) for upcoming datasets and standards support, and share your coverage requests with us at [support@learningcommons.org](mailto:support@learningcommons.org) ↗.
</Accordion>

<Accordion title="How long does integration take?">
  You can get up and running with Knowledge Graph in minutes, using one of our [4 access methods](/knowledge-graph/understanding-knowledge-graph/introduction#how-to-access-knowledge-graph).

  Check out our [Quickstart](/knowledge-graph/getting-started/quickstart#steps) for more information.
</Accordion>

## Evaluators

<Accordion title="Why should our team integrate Evaluators?">
  AI often fails educators in predictable ways (e.g., grade-leveling text, aligning to standards, etc.).

  Our evaluators address this known credibility gap:

  * They are validated against [expert-annotated datasets](/evaluators/dataset/introduction) and grounded in human expertise, learning science, and academic standards
  * They don't just tell you what's "wrong" with your AI-generated content – they also provide actionable guidance on how to fill the gaps

  Check out [some common use cases](/evaluators/understanding-evaluators/introduction#when-to-use-evaluators) of Evaluators before getting started.
</Accordion>

<Accordion title="I already have an evaluation process – why should I integrate your evaluators?">
  Our evaluators allow you to incorporate standards-aligned educational data into your AI content generation pipeline – all without having to rely on slow and expensive human evaluation.

  Our evaluators are also interoperable with many industry tools, so you don't have to completely overhaul your tech stack:

  * [BrainTrust](https://www.braintrust.dev/) ↗
  * [LangSmith](https://smith.langchain.com/) ↗
  * [Arize](https://arize.com/) ↗
  * [LangWatch](https://langwatch.ai/) ↗
  * [Langfuse](https://langfuse.com/) ↗
</Accordion>

<Accordion title="Our team has unique requirements and constraints for evaluation. Will your evaluators meet our team-specific needs?">
  Most users' requirements can be generalized relatively easily, and it is unlikely that your team's unique setup will degrade the accuracy of our evaluators' output.

  Reach out to [support@learningcommons.org](mailto:support@learningcommons.org) ↗ if you have further questions about integration.
</Accordion>

<Accordion title="What evaluators and datasets are available now?">
  We currently provide the following [evaluator families](/evaluators/understanding-evaluators/core-concepts#evaluator-family) and [evaluator datasets](/evaluators/understanding-evaluators/core-concepts#evaluator-dataset):

  |                        |                                                                                                                                              |
  | :--------------------- | :------------------------------------------------------------------------------------------------------------------------------------------- |
  | **Evaluator families** | [Literacy evaluators](/evaluators/literacy-evaluators/introduction)<br />[Feedback evaluators](/evaluators/feedback-evaluators/introduction) |
  | **Evaluator datasets** | [Literacy](/evaluators/dataset/literacy)<br />Feedback (Coming soon)                                                                         |

  Check out our [Roadmap](/evaluators/understanding-evaluators/roadmap) for upcoming evaluators and datasets.
</Accordion>

<Accordion title="How long does integration take?">
  You can get up and running with Evaluators in minutes, using one of our [3 access methods](/evaluators/understanding-evaluators/introduction#how-to-access-evaluators).

  Check out our [Quickstart](/evaluators/getting-started/quickstart#steps) for more information.
</Accordion>