feat: Add Interview Preparation AgentKit

[HimanshuSaxena12]

🎯 Interview Preparation Coach — AI-Powered Interview Evaluator

Stop guessing. Start winning.

Land your dream job with an AI coach that thinks like a senior hiring manager. Paste your answer, and in seconds get brutally honest, structured feedback that tells you exactly what's working, what's not, and how to say it better.
Whether it's a behavioral question about teamwork and conflict, or a technical deep-dive into your skills — this agent evaluates both dimensions simultaneously, scoring your response out of 10 and delivering actionable insights you can apply right now.
No fluff. No generic tips. Just real feedback that prepares you for the room.

Use it for:

💼 Mock interview practice
📄 Answer refinement before big interviews
🧠 Understanding what recruiters actually look for
🚀 Turning average answers into standout responses

• Added a new "Interview Preparation Coach" AgentKit that provides AI-powered evaluation of interview answers modeled after a senior hiring manager
• Includes dual evaluation of answers across behavioral and technical dimensions, each producing a 1-10 score, strengths, improvements, and suggested better answers
• Configured to use Groq's llama-3.1-8b-instant model via Lamatic InstructorLLM
• Flow accepts three inputs: job description, resume, and user answer
• Added complete kit structure: environment configuration, documentation, kit metadata, flow definition, input/output schemas, and two parallel LLM evaluation nodes (Behaviour_Prep and Technical_Prep)
• Provides structured JSON feedback combining results from both evaluation dimensions

[coderabbitai]

Caution

Review failed

Pull request was closed or merged during review

📝 Walkthrough

Walkthrough

A new Interview Preparation Coach kit is being added to the codebase, featuring a complete AI-powered interview evaluator. The kit includes flow definitions, configuration files, environment setup, and comprehensive documentation for evaluating user interview answers on behavioral and technical dimensions using dual LLM evaluation nodes.

Changes

Cohort / File(s)	Summary
Configuration & Setup kits/assistant/interview-preparation/interview-prep-kit/.env.example, kits/assistant/interview-preparation/interview-prep-kit/config.json	Added environment variable templates and root kit configuration defining the Interview Preparation assistant with Groq LLM integration, mandatory workflow step, and feature set for dual-dimension answer evaluation.
Documentation kits/assistant/interview-preparation/interview-prep-kit/README.md, kits/assistant/interview-preparation/interview-prep-kit/flows/interview-evaluator/README.md	Added kit-level and flow-level documentation describing setup, prerequisites, usage examples, API payloads, and flow architecture for the interview evaluator.
Flow Definition kits/assistant/interview-preparation/interview-prep-kit/flows/interview-evaluator/config.json, kits/assistant/interview-preparation/interview-prep-kit/flows/interview-evaluator/meta.json, kits/assistant/interview-preparation/interview-prep-kit/flows/interview-evaluator/inputs.json	Added complete flow definition with two InstructorLLM nodes (Behaviour_Prep and Technical_Prep) configured to evaluate interview answers using groq/llama-3.1-8b-instant, along with input schema (jobDescription, resume, userAnswer) and flow metadata mapping outputs to behavioral/technical scores and improvement suggestions.

Sequence Diagram

sequenceDiagram
    actor Client
    participant API as API Trigger
    participant Behaviour as Behaviour_Prep<br/>(LLM Node)
    participant Technical as Technical_Prep<br/>(LLM Node)
    participant Response as API Response

    Client->>API: POST (jobDescription, resume, userAnswer)
    activate API
    API->>Behaviour: Evaluate behavioral aspects
    activate Behaviour
    Behaviour-->>API: {score, strengths, improvements, better_answer}
    deactivate Behaviour
    API->>Technical: Evaluate technical aspects
    activate Technical
    Technical-->>API: {score, strengths, improvements, better_answer}
    deactivate Technical
    API->>Response: Map behavioral_* & technical_* fields
    activate Response
    Response-->>Client: Combined evaluation results
    deactivate Response
    deactivate API

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Estimated code review effort

🎯 3 (Moderate) | ⏱️ ~25 minutes

Suggested reviewers

• amanintech

🚥 Pre-merge checks | ✅ 3

✅ Passed checks (3 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title 'feat: Add Interview Preparation AgentKit' accurately summarizes the main change—adding a new Interview Preparation AgentKit with all supporting configuration, flow definitions, and documentation files.
Docstring Coverage	✅ Passed	No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check.

_{✏️ Tip: You can configure your own custom pre-merge checks in the settings.}

✨ Finishing Touches

🧪 Generate unit tests (beta)

• Create PR with unit tests

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[d-pamneja]

Do not see any app or demo link. If this is a kit contributions, kindly make this as an application and then submit it.

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