name: interview
description: >
Structured human-agent Q&A via HTML or TUI forms. Use when you need clear
yes/no/refine decisions from the user on multiple items. Agent provides
recommendations, human validates or overrides.
allowed-tools: Bash, Read
triggers:
- interview user
- get user feedback
- review items with user
- human review
- ask user to review
- structured Q&A
metadata:
short-description: Structured Q&A forms (HTML/TUI) with agent recommendations

Interview Skill

Structured human-agent Q&A via forms. Agent leads with recommendations, human validates.

Quick Start

# TUI mode (terminal)
.pi/skills/interview/run.sh --mode tui --file questions.json

# HTML mode (browser)
.pi/skills/interview/run.sh --mode html --file questions.json

# Auto-detect (HTML if browser available, else TUI)
.pi/skills/interview/run.sh --file questions.json

Question Format

{
  "title": "Review Distilled Q&As",
  "context": "Reviewing extracted knowledge from STITCH paper",
  "questions": [
    {
      "id": "q1",
      "text": "Q: What is STITCH?\nA: Intent-aware memory indexing...",
      "type": "yes_no_refine",
      "recommendation": "keep",
      "reason": "Directly relevant to plan_state design"
    },
    {
      "id": "q2",
      "text": "Q: What dataset sizes were used?\nA: 100 small, 200 large...",
      "type": "yes_no_refine",
      "recommendation": "drop",
      "reason": "Implementation detail, not generalizable"
    }
  ]
}

Question Types

Response Format

{
  "session_id": "abc123",
  "completed": true,
  "duration_seconds": 45,
  "responses": {
    "q1": {"decision": "accept", "value": "keep"},
    "q2": {"decision": "override", "value": "keep", "note": "Actually useful for benchmarking"}
  }
}

Modes

HTML Mode

• Opens browser with Tailwind-styled form
• Auto-saves to localStorage
• Keyboard navigation (Tab, Enter, Escape)
• Returns when form submitted or timeout

TUI Mode

• Textual-based terminal UI
• Rich formatting with colors
• Arrow keys + Enter navigation
• Works over SSH/headless

Integration Example

from interview import Interview

# Create questions with agent recommendations
questions = [
    {
        "id": "qa_1",
        "text": "Q: What is STITCH?\nA: Intent-aware memory...",
        "type": "yes_no_refine",
        "recommendation": "keep",
        "reason": "Relevant to our memory architecture"
    }
]

# Run interview
interview = Interview(title="Review Paper Q&As")
responses = interview.run(questions, mode="auto")

# Process responses
for qid, response in responses["responses"].items():
    if response["value"] == "keep":
        store_qa(qid)

Session Recovery

Sessions auto-save to .pi/skills/interview/sessions/. If interrupted:

# Resume last session
.pi/skills/interview/run.sh --resume

# Resume specific session
.pi/skills/interview/run.sh --resume abc123

Environment Variables