tutor-service/.planning/phases/002-diagnostic-interview-loop/002-PLAN.md

Phase 2 Plan: Diagnostic Interview Loop

Status: Ready for execution Phase Goal: Prove the first job-seeker loop from role selection through graded diagnostic interview.

Requirements Covered

• INT-01: User can select target role, stack, and interview timeline.
• INT-02: User can complete a diagnostic technical interview.
• INT-03: System can generate role-specific interview questions.
• INT-04: System can grade user answers against explicit rubrics.
• INT-05: System can ask targeted follow-up questions for weak answers.
• INT-06: System preserves original answers and grading evidence.

Tasks

1. Add interview domain package

• Create internal/interview.
• Define session, question, answer, and store types.
• Add in-memory store implementation.
• Add backend developer diagnostic question catalog.

2. Add diagnostic service

• Create session from target role, stack, and optional interview timeline.
• Select first diagnostic questions from the backend developer track.
• Record submitted answers.
• Invoke workflows.Runner.GradeInterviewAnswer.
• Attach typed grading result and evidence to the answer record.

3. Add HTTP endpoints

• POST /api/v1/diagnostic-sessions
• GET /api/v1/diagnostic-sessions/{id}
• POST /api/v1/diagnostic-sessions/{id}/answers

4. Extend workflow stub

• Return deterministic typed grades.
• Include follow-up recommendation for weak answers.
• Include evidence references.

5. Add tests

• Domain tests for session creation and answer grading.
• HTTP tests for create/get/answer flow.
• Existing config/workflow tests remain passing.

6. Update GSD/OpenSpec state

• Mark INT-01 through INT-06 complete if all success criteria pass.
• Add Phase 2 summary and verification artifacts.

Verification

gofmt -w cmd internal
go test ./...
openspec validate bootstrap-job-tutor-platform --strict

Run Go line-count check and confirm every manually authored Go file is at or below 600 lines.

Out of Scope

• Database persistence.
• Authentication.
• Real LLM grading.
• Durable learner memory.
• Progression map.
• Frontend.

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Plan created: 2026-04-26