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

# Cookbook: EdTech tutor

> Build tutoring, exam-prep, and learning apps with the EdTech domain schema.

Use this cookbook when your product teaches, tutors, coaches students, or personalizes learning paths.

The EdTech schema keeps the same SDK calls as the general engine, but adds structured student memory such as grade level, curriculum, weak topics, learning style, exam context, and forgetting-stage review signals.

## Enable the domain

Use the tenant domain endpoint during onboarding or from an admin settings page.

```http theme={null}
PATCH /v1/tenant/domain-schema
Authorization: ApiKey mem_...
Content-Type: application/json
```

```json theme={null}
{
  "domain_schema": "edtech"
}
```

You can check the active domain:

```http theme={null}
GET /v1/tenant/domain-schema
Authorization: ApiKey mem_...
```

## Add a tutoring session

```python theme={null}
import os

from memoryos import Memory

mem = Memory(api_key=os.environ["MEMORYOS_API_KEY"])

result = mem.add(
    external_user_id="student_123",
    messages=[
        {
            "role": "user",
            "content": "I am in Class 10 CBSE. My boards are in March. Algebra is okay, but I keep forgetting trigonometry identities.",
        },
        {
            "role": "assistant",
            "content": "We will revise trigonometry identities with CBSE Class 10 examples and quick recall practice.",
        },
    ],
    metadata={"source": "lesson", "subject": "math"},
)

print(result.status)
```

MemoryOS writes generic memories and updates the EdTech overlay internally.

## Retrieve lesson context

Call `get()` immediately before your model call.

```python theme={null}
memories = mem.get(
    query="teach this student trigonometry identities",
    external_user_id="student_123",
    limit=8,
    context_max_tokens=700,
)

system_prompt = "You are a patient math tutor."
if memories.has_context:
    system_prompt = f"{system_prompt}\n\n{memories.system_prompt_addition}"
```

For an EdTech tenant, `system_prompt_addition` can include student-specific tutoring context before the normal memory bullets.

## Build a student dashboard

Use `get_edtech_profile()` only when your UI needs structured profile fields. Normal tutoring calls should use `get()`.

```python theme={null}
profile = mem.get_edtech_profile("student_123")

if profile:
    print(profile.grade_level)
    print(profile.board_or_curriculum)
    print(profile.exam_name, profile.exam_date)
    print(profile.weak_topics[:3])
    print(profile.forgetting_stages)
```

TypeScript:

```ts theme={null}
const profile = await mem.getEdTechProfile("student_123");

if (profile?.hasExamContext) {
  console.log(profile.examName, profile.examDate);
}

console.log(profile?.weakTopics.slice(0, 3));
```

## Suggested product moments

Call `add()` after:

* the student introduces goals, grade, curriculum, exam, or deadline
* the tutor observes a strong topic, weak topic, misconception, or concept gap
* the student changes explanation style or language preference
* a lesson ends with meaningful progress or review needs

Call `get()` before:

* generating the next tutoring response
* building a practice plan
* choosing review questions
* preparing an exam-readiness summary

## Conflict behavior

The EdTech router sends personal student facts back to the student for clarification and routes workspace-level facts to tenant review.

| Example                                     | Expected route             |
| ------------------------------------------- | -------------------------- |
| Exam date changed from March 10 to March 15 | User session clarification |
| Student changed from Class 10 to Class 11   | User session clarification |
| Institution curriculum changed              | Tenant review              |
| Student prefers Hinglish explanations now   | Personal preference update |

## Data boundaries

Keep your own source-of-truth academic records in your product database. MemoryOS stores memory extracted from interactions and makes it useful for AI context.

Use your product database for:

* enrollment
* payment status
* official grades
* institution rosters
* parent or guardian records

Use MemoryOS for:

* learning preferences
* weak and strong topics
* tutoring context
* exam goals mentioned in conversation
* review urgency and personalized context

## Related pages

* [Domain schemas](/concepts/domain-schemas)
* [GET /v1/memories/edtech-profile](/api-reference/edtech-profile)
* [EdTech domain guide](/guides/edtech-domain)