Overview
Interviewly is an AI-powered mock interview platform designed to help job candidates prepare for technical and behavioral interviews. The platform uses advanced natural language processing to analyze job descriptions, generate role-specific interview questions, and provide comprehensive feedback on candidate responses.
The API enables a four-step interview workflow: job description analysis, interview initialization, response submission with real-time evaluation, and final report generation. Each interview is personalized based on the analyzed job requirements, creating a realistic and tailored preparation experience.
Ideal users include job seekers preparing for interviews, recruitment platforms offering candidate assessment features, corporate training teams, and educational institutions building interview preparation modules.
Usage
Example: Complete Interview Workflow
Step 1: Analyze Job Description
POST /api/v1/analyze-jd
Content-Type: application/json
{
"job_description": "Senior Full Stack Engineer - 5+ years experience with React, Node.js, and AWS. Must have experience with microservices architecture and CI/CD pipelines."
}
Response:
{
"success": true,
"session_id": "sess_a1b2c3d4e5f6",
"analysis": {
"required_skills": ["React", "Node.js", "AWS", "Microservices", "CI/CD"],
"experience_level": "Senior",
"role_type": "Full Stack Engineer"
},
"estimated_questions": 6,
"message": "Job description analyzed successfully"
}
Step 2: Start Interview
POST /api/v1/start-interview
Content-Type: application/json
{
"session_id": "sess_a1b2c3d4e5f6",
"user_id": 12345
}
Response:
{
"success": true,
"first_question": "Tell me about your experience with microservices architecture. Can you describe a specific project where you designed or worked with microservices?",
"question_number": 1,
"total_questions": 6,
"time_limit_minutes": 3
}
Step 3: Submit Response
POST /api/v1/submit-response
Content-Type: application/json
{
"session_id": "sess_a1b2c3d4e5f6",
"question_number": 1,
"user_response": "I led the migration of our monolithic application to microservices using Node.js. We split into 8 independent services with their own databases, managed through Kubernetes on AWS ECS.",
"response_time_seconds": 45,
"transcription_confidence": 0.98
}
Response:
{
"success": true,
"next_question": "What challenges did you face during this migration and how did you overcome them?",
"question_number": 2,
"feedback": "Strong answer demonstrating practical microservices experience. Consider adding more details about deployment strategies.",
"interview_complete": false
}
Step 4: End Interview & Download Report
POST /api/v1/end-interview
Content-Type: application/json
{
"session_id": "sess_a1b2c3d4e5f6"
}
Response:
{
"success": true,
"overall_score": 78,
"report_url": "https://api.toolweb.in/api/v1/download/sess_a1b2c3d4e5f6",
"message": "Interview completed. Report generated successfully."
}
Endpoints
GET /
Purpose: API health check
Parameters: None
Response: 200 OK with service status
GET /status
Purpose: Detailed health check with service diagnostics
Parameters: None
Response: 200 OK with detailed health information
POST /api/v1/analyze-jd
Purpose: Analyze job description and initialize interview session
Parameters:
| Name | Type | Required | Description |
|---|
| job_description | string | Yes | Full job description text to analyze |
Response Shape:
{
"success": boolean,
"session_id": string,
"analysis": {
"required_skills": string[],
"experience_level": string,
"role_type": string
},
"estimated_questions": integer,
"message": string
}
POST /api/v1/start-interview
Purpose: Initialize interview session and generate first question
Parameters:
| Name | Type | Required | Description |
|---|
| session_id | string | Yes | Session ID from analyze-jd response |
| user_id | integer | Yes | Unique identifier for the candidate |
Response Shape:
{
"success": boolean,
"first_question": string,
"question_number": integer,
"total_questions": integer,
"time_limit_minutes": integer
}
POST /api/v1/submit-response
Purpose: Submit candidate response, evaluate with Claude AI, and generate next question
Parameters:
| Name | Type | Required | Description |
|---|
| session_id | string | Yes | Active session ID |
| question_number | integer | Yes | Current question number |
| user_response | string | Yes | Candidate's answer text |
| response_time_seconds | integer | No | Time taken to respond in seconds |
| transcription_confidence | number | No | Confidence score (0-1) if voice-transcribed |
Response Shape:
{
"success": boolean,
"next_question": string | null,
"question_number": integer | null,
"feedback": string | null,
"interview_complete": boolean
}
POST /api/v1/end-interview
Purpose: Terminate interview, generate comprehensive evaluation report, and create PDF with download URL
Parameters:
| Name | Type | Required | Description |
|---|
| session_id | string | Yes | Session ID to end |
Response Shape:
{
"success": boolean,
"overall_score": integer,
"report_url": string,
"message": string
}
GET /api/v1/download/{session_id}
Purpose: Download the interview report PDF
Parameters:
| Name | Type | Required | Description |
|---|
| session_id | string (path) | Yes | Session ID of completed interview |
Response: PDF file download
Pricing
| Plan | Calls/Day | Calls/Month | Price |
|---|
| Free | 5 | 50 | Free |
| Developer | 20 | 500 | $39/mo |
| Professional | 200 | 5,000 | $99/mo |
| Enterprise | 100,000 | 1,000,000 | $299/mo |
About
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References
