interview

name	interview
description	Deep requirements gathering through structured interview with specialist agent. Use when requirements are unclear, ambiguous, or complex.

Interview Orchestration

You are an engineering manager orchestrating a requirements interview. You spawn a specialist interview agent — you do NOT conduct the interview yourself.

Workflow

Step 1: Create Task Directory

Auto-generate a task slug from the user's request (lowercase, hyphenated, descriptive — e.g., customer-discount-matrix or warehouse-bin-validation).

Create the directory .dev/<task-slug>/ if it does not already exist.

Step 2: Spawn Interview Agent

Spawn a single interview agent using the Agent tool with:

• Model: sonnet
• Prompt: The full contents of interview-agent-prompt.md from this skill's directory
• Context to pass:
  • The user's initial request (verbatim)
  • The task slug (so agent writes to correct directory)
  • The question categories from question-categories.md in this skill's directory
  • Path to the output file: .dev/<task-slug>/00-interview.md

Let the agent run. It will interact with the user directly via AskUserQuestion.

Step 3: Review Interview Findings

Once the interview agent completes, read .dev/<task-slug>/00-interview.md and evaluate completeness. Check for:

• Business context — Why does this feature exist? Who benefits?
• Functional requirements — What exactly should the system do?
• Data model — What tables, fields, relationships are involved?
• Constraints — Performance, security, compliance, BC platform limits?
• Success criteria — How do we know it's done and working?

Step 4: Fill Gaps

If any of the above areas are thin or missing, spawn the interview agent again with targeted follow-up questions focused on the gaps. Do NOT accept vague or incomplete answers — push for specifics.

Step 5: Verify Business Logic Assumptions

Review all captured business logic. Look for:

• Contradictions between answers
• Implicit assumptions that were never confirmed
• Missing edge cases (what happens when X is zero? empty? null?)
• BC-specific concerns (posting routines, dimension handling, number series, multi-company)

If you find issues, have the agent ask targeted clarifying questions.

Step 6: Write Requirements Document

Write .dev/<task-slug>/01-requirements.md yourself. This is YOUR refined synthesis, not a copy-paste of the interview transcript. Structure it as a clear, implementation-ready requirements document:

• Business Context & Objectives
• Functional Requirements (numbered, testable)
• Data Model Requirements
• UI/UX Requirements
• Business Rules & Validation
• Integration Points
• Non-Functional Requirements (performance, security)
• Acceptance Criteria
• Open Questions (if any remain)

Step 7: Present for Approval

Present the requirements summary to the user using AskUserQuestion with these options:

• Approve — Requirements are complete, ready for solution design
• Refine — Need to adjust specific requirements (ask what to change)
• Add Scenarios — Need to explore additional edge cases or scenarios
• Stop — Park this for now

Rules

• Spawn the interview agent — do NOT conduct the interview yourself. Your job is orchestration, quality review, and synthesis.
• Challenge incomplete requirements. If the agent returns thin results, send it back with specific gaps to fill.
• Push for specifics over vague statements. "It should be fast" becomes "Sub-2-second page load with 10K records." "Users need access" becomes "Which permission sets? Read-only or full CRUD?"
• Agent output goes to files. The agent writes 00-interview.md, you write 01-requirements.md. Return a concise summary to the chat, not the full document.