Build Your
Personal AI OS

---
name: interview
description: Interview user to understand requirements before implementation
argument-hint: <task-description>
context: fork
agent: general-purpose
---

## Purpose

Thoroughly understand requirements for: $ARGUMENTS

## Interview Workflow

**CRITICAL: You MUST use the AskUserQuestion tool throughout this interview process.**

Before implementing any task, conduct a structured interview using the **AskUserQuestion tool** to fully understand the request.

### Phase 1: Initial Understanding

Ask focused questions to explore:

1. **Goals and Success Criteria**
   - What does "done" look like?
   - What problem are we solving?
   - Who is the end user?
   - How will success be measured?

2. **Technical Constraints**
   - Are there specific technologies or patterns to use/avoid?
   - Performance requirements?
   - Compatibility requirements?
   - Security considerations?

3. **UI/UX Expectations**
   - What should the user experience be?
   - Mobile vs desktop considerations?
   - Accessibility requirements?
   - Error handling and edge cases?

4. **Tradeoffs and Priorities**
   - What tradeoffs are acceptable?
   - Speed vs quality vs completeness?
   - What's a must-have vs nice-to-have?
   - Timeline or deadline considerations?

5. **Ambiguities and Unknowns**
   - What parts are unclear or underspecified?
   - What assumptions need validation?
   - What could go wrong?

### Phase 2: Deep Dive

**Use the AskUserQuestion tool to:**

- Ask one focused question at a time
- Build on answers with relevant follow-ups
- Dig deeper when answers are vague or suggest hidden complexity
- Clarify contradictions or conflicting requirements
- Explore edge cases that may not be obvious

### Phase 3: Confirmation

Once you have sufficient clarity:

1. **Summarize your understanding** in structured format:

   ## Requirements Summary

   ### Goal
   [what we're building]

   ### Success Criteria
   - [criterion 1]
   - [criterion 2]

   ### Technical Approach
   [how we'll implement it]

   ### Constraints
   - [constraint 1]

   ### Edge Cases to Handle
   - [case 1]

   ### Out of Scope
   - [what we're NOT doing]

2. **Ask for confirmation**: "Does this capture your requirements correctly?"
3. **Wait for explicit approval** before proceeding

### Phase 4: Implementation Planning

After confirmation:
- Create a detailed implementation plan
- Break down into smaller tasks if needed
- Identify files to create/modify
- Plan testing approach

## Notes

- **MUST use AskUserQuestion tool**: All questions must be asked via the tool
- **Quality over speed**: Better to ask too many questions than implement the wrong thing
- **No assumptions**: When in doubt, ask
- **Document decisions**: Capture the "why" behind choices

---
name: trend-research
description: Scan Reddit and HN for trending AI/engineering topics, deep-dive top 3, and generate LinkedIn post angles
argument-hint: [topic list override or "default" for standard list]
---

## Purpose

Discover what's trending RIGHT NOW across AI/engineering communities. Surface scan all topics, deep-dive the top 3, and generate LinkedIn post angles with source links.

Arguments: $ARGUMENTS

## Steps

### 1. Determine Topic List

If $ARGUMENTS provides custom topics, use those. Otherwise use this default list:

- Claude Code / Cursor / Codex / Devin
- MCP (Model Context Protocol)
- AI subagents / multi-agent systems
- LLM orchestration / agent orchestration
- Vibe coding / AI coding assistants
- Agent memory / context window management
- Tool use / function calling
- LLMOps / AI infrastructure
- Platform engineering + AI

### 2. Surface Scan

For each topic, run ONE fast search:
- `site:reddit.com "{topic}" after:2025-01-01`
- `site:news.ycombinator.com "{topic}"`

Score each topic 1-3 on:
- Volume of recent threads
- Engagement levels
- Controversy or strong opinions present

### 3. Deep Dive

Pick the TOP 3 scoring topics. For each one, run the full search suite:
- `site:reddit.com "{topic}" (discussion OR opinion OR experience)`
- `site:reddit.com "{topic}" (hot take OR rant OR controversy)`
- `site:reddit.com/r/devops OR r/programming OR r/ExperiencedDevs "{topic}"`
- `site:news.ycombinator.com "{topic}"`
- `site:news.ycombinator.com "Ask HN" "{topic}"`

For each thread found, extract: title, subreddit/source, upvotes, comments, date, URL, key takeaway, and a LinkedIn angle.

### 4. Output Format

**Trending This Week**
Ranked list of all topics by momentum score with one-line reason why.

**Deep Dive: [Topic 1]**
- **Trend Summary:** 3 bullets on what the community is saying
- **Top Threads (5-8):**
  - **[Title]** - r/subreddit or HN - upvotes/comments - date
  - → Takeaway: one sentence
  - → LinkedIn angle: one sentence hook idea
  - → URL

*(same structure for Topics 2 & 3)*

**Top 3 LinkedIn Post Angles Across All Topics**
- **Hook:** scroll-stopping opening line
- **Tension:** core argument or contradiction
- **Why it lands:** resonance with DevOps/engineering managers

**Signal vs. Sentiment Check**
2-3 sentences comparing where Reddit/HN hype and adoption data agree or diverge.
Highlight overhyped (high sentiment, low adoption) or hidden momentum (surging adoption, quiet sentiment).

### 5. Ask for Approval

Ask: "Does this look right? Save to vault?"

- If yes - proceed to step 6
- If adjustments - apply edits, show updated section, ask again
- If no / discard - stop here, nothing saved

### 6. Save Results

Ask user where to save the note.

Frontmatter:
  type: research
  source: trend-scan
  topics-scanned: <number of topics>
  top-3: [topic-1-slug, topic-2-slug, topic-3-slug]
  tags: [linkedin, trend-research, reddit, hackernews]
  created: <today's date YYYY-MM-DD>

### 7. Next Steps

Ask: "Which of these 3 topics do you want to go deeper on?"