Syllabus Skills Extraction

Extract skills from course syllabi. Upload PDF files for analysis to identify skills students will develop. Supports asynchronous processing.

Submit syllabus for skills extraction

post

Submits a syllabus PDF for extraction. Upload the PDF file directly.

This is an asynchronous operation. The response includes a taskId that you can use to poll for status.

Processing Steps:

1. Document parsing and text extraction

2. Course metadata identification

3. Skills identification using MSL taxonomy

4. Proficiency level assignment

5. Confidence scoring and validation

Typical processing time is 30-90 seconds depending on document length.

Supported File Types: PDF only (application/pdf) Maximum File Size: 25MB

Authorizations

bearerAuth & customerKey

AuthorizationstringRequired

Platform API key passed as a Bearer token in the Authorization header. Use your test key for the testing environment and your production key for production.

X-Customer-KeystringRequired

End-customer API key identifying which customer is making the request. Required for all production calls. Not required for the testing environment. Provision these in the Embedded API Portal.

Body

multipart/form-data

filestring · binaryRequired

The syllabus PDF file to process

metadatastringOptional

JSON string containing optional course metadata. Fields match the metadata extraction output: title, courseCode, instructor, description, sectionName, sectionDescription. User-provided values override AI-extracted values. Example: {"title": "Intro to CS", "courseCode": "CS101", "instructor": "Dr. Smith"}

Example: {"title": "Intro to CS", "courseCode": "CS101", "instructor": "Dr. Smith"}

Responses

202

Extraction task created and queued for processing

application/json

400

Invalid request parameters

application/json

401

Missing or invalid API key

application/json

403

Access denied (insufficient permissions or quota exceeded)

application/json

429

Rate limit exceeded

application/json

500

Internal server error

application/json

post

/skills-extraction/syllabus

HTTPcURLJavaScriptPython

POST /v1/skills-extraction/syllabus HTTP/1.1
Host: embedded-api-sandbox.mapademics.com
Authorization: Bearer YOUR_SECRET_TOKEN
X-Customer-Key: YOUR_API_KEY
Content-Type: multipart/form-data
Accept: */*
Content-Length: 117

{
  "file": "binary",
  "metadata": "{\"title\": \"Intro to CS\", \"courseCode\": \"CS101\", \"instructor\": \"Dr. Smith\"}"
}

{
  "object": "text",
  "data": {
    "taskId": "task_def456uvw",
    "extractionId": "syl_ghi789rst",
    "status": "queued",
    "createdAt": "2025-01-30T12:00:00Z"
  },
  "meta": {
    "requestId": "req_abc123xyz",
    "timestamp": "2025-01-30T12:00:00Z"
  }
}

Check extraction task status

get

Retrieves the current status of a syllabus extraction task. Poll this endpoint to track progress until status is completed or failed.

Status Values:

• queued - Task is waiting to be processed

• processing - Task is currently being processed

• completed - Extraction finished successfully

• failed - Extraction failed (see error for details)

Authorizations

bearerAuth & customerKey

AuthorizationstringRequired

Platform API key passed as a Bearer token in the Authorization header. Use your test key for the testing environment and your production key for production.

X-Customer-KeystringRequired

End-customer API key identifying which customer is making the request. Required for all production calls. Not required for the testing environment. Provision these in the Embedded API Portal.

Path parameters

taskIdstringRequired

Task identifier returned from syllabus upload

Example: {"value":"task_clx8k7t5u0003tklvyzbc789","summary":"Completed task"}

Responses

200

Task status retrieved

application/json

401

Missing or invalid API key

application/json

403

Access denied (insufficient permissions or quota exceeded)

application/json

404

Resource not found

application/json

429

Rate limit exceeded

application/json

500

Internal server error

application/json

get

/skills-extraction/syllabus/tasks/{taskId}

HTTPcURLJavaScriptPython

GET /v1/skills-extraction/syllabus/tasks/{taskId} HTTP/1.1
Host: embedded-api-sandbox.mapademics.com
Authorization: Bearer YOUR_SECRET_TOKEN
X-Customer-Key: YOUR_API_KEY
Accept: */*

{
  "object": "extraction_task",
  "data": {
    "taskId": "task_def456uvw",
    "extractionId": "syl_ghi789rst",
    "status": "processing",
    "createdAt": "2025-01-30T12:00:00Z",
    "updatedAt": "2025-01-30T12:00:45Z"
  },
  "meta": {
    "requestId": "req_jkl012mno",
    "timestamp": "2025-01-30T12:00:50Z"
  }
}

Get extraction results

get

Retrieves the extracted skills and metadata from a processed syllabus. Only available after the extraction task has completed successfully.

Authorizations

bearerAuth & customerKey

AuthorizationstringRequired

Platform API key passed as a Bearer token in the Authorization header. Use your test key for the testing environment and your production key for production.

X-Customer-KeystringRequired

End-customer API key identifying which customer is making the request. Required for all production calls. Not required for the testing environment. Provision these in the Embedded API Portal.

Path parameters

extractionIdstringRequired

Extraction identifier from completed task

Example: {"value":"syl_clx8g4m2n0001ex7tuvwab12","summary":"CIS 115 - Intro to Programming"}

Responses

200

Extraction results retrieved

application/json

401

Missing or invalid API key

application/json

403

Access denied (insufficient permissions or quota exceeded)

application/json

404

Resource not found

application/json

429

Rate limit exceeded

application/json

500

Internal server error

application/json

get

/skills-extraction/syllabus/{extractionId}

HTTPcURLJavaScriptPython

GET /v1/skills-extraction/syllabus/{extractionId} HTTP/1.1
Host: embedded-api-sandbox.mapademics.com
Authorization: Bearer YOUR_SECRET_TOKEN
X-Customer-Key: YOUR_API_KEY
Accept: */*

{
  "object": "syllabus_extraction",
  "data": {
    "extractionId": "syl_ghi789rst",
    "filename": "CS101-Fall2025-Syllabus.pdf",
    "metadata": {
      "courseName": "Introduction to Computer Science",
      "courseCode": "CS101",
      "courseDescription": "An introductory course covering programming fundamentals",
      "sectionName": "Section A - Fall 2025",
      "sectionDescription": null,
      "instructor": "Dr. Jane Smith"
    },
    "skills": [
      {
        "skillId": "msl_skill_0127",
        "level": 2,
        "mode": "explicit",
        "rationale": "Learning objective: Students will write programs in Python"
      },
      {
        "skillId": "msl_skill_0412",
        "level": 3,
        "mode": "implicit",
        "rationale": "Multiple assignments require algorithmic thinking and debugging"
      }
    ],
    "statistics": {
      "totalSkillsIdentified": 12,
      "explicitSkills": 8,
      "implicitSkills": 4
    },
    "createdAt": "2025-01-30T12:00:00Z",
    "completedAt": "2025-01-30T12:01:15Z"
  },
  "meta": {
    "requestId": "req_vwx678yza",
    "timestamp": "2025-01-30T12:05:00Z"
  }
}