365 lines
11 KiB
Markdown
365 lines
11 KiB
Markdown
---
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name: research
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description: Multi-LLM parallel research with query decomposition and synthesis
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triggers:
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- "research"
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- "find out about"
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- "investigate"
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- "look into"
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- "what do you know about"
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- "deep dive"
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- "analyze"
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- "compare"
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- "find information"
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- "learn about"
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allowed-tools: Read, Bash, WebSearch, WebFetch, Task
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version: 0.1.0
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---
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# Research Skill
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Discovery-driven, exhaustive research using parallel LLM agents for comprehensive, current information gathering.
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## Core Principles
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**CRITICAL:** These principles define how research works.
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### 1. Discovery-Driven, Not List-Driven
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- Find the BEST sources, not just known sources
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- Don't limit to predefined source lists
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- The internet is huge - explore it
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- Value is in finding what user doesn't already know
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### 2. Context-Aware
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- Load user's domain context from preferences
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- Research is RELEVANT to their specific situation
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- But context doesn't limit WHERE you search
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### 3. Exhaustive
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- No time limits - can take 30 minutes to 3 hours
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- Don't stop at first page of results
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- Keep going until topic is exhausted
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- Follow promising links deeper
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### 4. Multimedia
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- Not just text articles
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- Videos (YouTube), TikTok, podcasts
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- Real user experiences from forums
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### 5. Highly Cited
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- Every claim must have a citation
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- Multiple sources for important claims
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- Note when sources conflict
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### 6. Clarifying Questions First
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Before diving into research, ask deep, thought-provoking questions to understand:
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- What's the actual goal? (not just the surface request)
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- What constraints exist? (budget, time, preferences)
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- What would success look like?
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- What have they already tried or considered?
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- Are there hidden requirements?
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Example: "Research Japan ski trip" should prompt:
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- "What skill level are you and Carrie? Blue runs, black diamonds?"
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- "Is après-ski culture important, or pure skiing focus?"
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- "Do you need English-friendly areas, or comfortable with Japanese-only?"
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- "Any specific dates that are fixed vs flexible?"
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- "Besides skiing, anything else you want to do (onsen, food tours)?"
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## Domain Context Loading
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Research automatically loads relevant context from preferences based on detected domain.
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### How It Works
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1. Detect domain from query (travel, shopping, work, etc.)
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2. Load `research_domains.[domain]` from preferences
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3. Load referenced context keys
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4. Fetch any dynamic data (point balances, etc.)
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5. Apply domain-specific research patterns
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### Available Domains
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- **travel** - Loads loyalty programs, credit cards, ski passes, fetches point balances
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- **work_education** - Loads PSD context, CoSN membership, K-12 patterns
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- **shopping** - Price comparison, quality patterns
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- **ai_coding** - Tech stack, GitHub/HN patterns
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- **consulting** - Strategic recommendations patterns
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### Dynamic Data Fetching
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For travel research, use browser-control to fetch current:
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- Marriott points balance
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- Alaska miles balance
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- Chase points balance
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- Active transfer bonus promotions
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## When to Activate
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Use this skill when user needs:
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- Current information (credit card perks, travel deals, policies)
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- Multi-perspective analysis (comparing options)
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- Deep investigation of complex topics
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- Fact-checking or verification
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- Market research or trend analysis
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## Travel Research Requirements
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**CRITICAL:** Travel research MUST include user-generated content:
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### Required Sections for Travel
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1. **User Reviews** - TripAdvisor, FlyerTalk, Reddit feedback
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2. **"What I Wish I Knew"** - Common mistakes and gotchas
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3. **Real Experiences** - Actual trip reports from similar travelers
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4. **Restaurant/Hotel Reviews** - With prices and quality feedback
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5. **Transportation Tips** - Real user experiences with logistics
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### Sources to Search
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- TripAdvisor reviews and forums
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- FlyerTalk (for points/miles properties)
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- Reddit (r/JapanTravel, r/skiing, r/churning, etc.)
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- Ski forums and trip reports
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- Points/miles blogs with personal reviews
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### Browser Access for Deep Research
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Use the **browser-control** skill to scrape full threads and reviews that require:
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- JavaScript rendering (Reddit, modern forums)
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- Authentication (FlyerTalk, logged-in content)
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- Dynamic content loading
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**Prerequisites:**
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1. Brave must be running: `cd skills/browser-control && ./scripts/launch-chrome.sh`
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2. User must be logged into relevant sites in the Brave Geoffrey profile
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**Available Scripts** (in `skills/browser-control/scripts/`):
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```bash
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# Navigate and get page content
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bun navigate.js "https://www.reddit.com/r/JapanTravel/comments/..."
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# Extract specific content
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bun extract.js "https://flyertalk.com/forum/thread" ".post-content" --all
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# Search travel sites directly
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bun search.js reddit "Hakuba ski resort tips"
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bun search.js flyertalk "Marriott Bonvoy Japan redemption"
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# Capture current page without navigating
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bun capture.js /tmp/screenshot.png
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```
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**When to Use Browser Control:**
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- Reddit threads (full comments, not just preview)
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- FlyerTalk forum posts (complete thread content)
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- Hotel/airline pages requiring login (availability, points pricing)
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- Sites that block web scraping but allow browsers
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### Research Tool Decision Tree
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**Start with WebSearch/WebFetch** for:
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- General facts and information
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- Blog posts and news articles
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- Static content that's publicly accessible
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- Quick lookups
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**Escalate to browser-control** when:
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- WebFetch returns truncated/incomplete content (JS-rendered sites)
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- Need authenticated access (user's Marriott/Alaska account)
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- Need real-time prices or availability
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- Forum threads show only previews
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- Site blocks scraping but allows browsers
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**Example Flow:**
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1. User asks: "What do people say about Westin Rusutsu?"
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2. Start with `WebSearch` for blog reviews
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3. Find promising Reddit/FlyerTalk threads
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4. Use `browser-control` to get full thread content
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5. Synthesize findings with citations
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## Citation Requirements
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**CRITICAL:** All research output MUST include citations.
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### Inline Citations
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Every factual claim must link to its source:
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- "The Westin Rusutsu costs 70,000 points peak ([Point Hacks](url))"
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- "Shinkansen to Nagano takes 1.5 hours ([Corritrip](url))"
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### Source Section
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Every research report must end with a complete "Sources" section listing all URLs used.
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### Why This Matters
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- User needs to verify information
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- Information changes frequently (credit card perks, prices)
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- Establishes credibility
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- Allows deeper exploration
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### No Citation = Don't Include
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If you can't cite a source for a claim, either:
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1. Find a source
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2. Mark it as "unverified"
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3. Don't include it
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## Architecture
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### Query Decomposition
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Break complex questions into 3-7 sub-queries covering different angles:
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- Factual/definitional
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- Comparative
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- Current state
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- Expert opinions
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- User experiences
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- Edge cases
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### Parallel Agent Execution
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Launch multiple researcher agents simultaneously:
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- **Perplexity** - Best for current web information, citations
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- **Gemini** - Good for multi-perspective synthesis
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- **OpenAI** - Strong structured analysis
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- **Claude** - Deep reasoning, nuanced analysis
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### Result Synthesis
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- Collect all findings
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- Identify consensus vs conflicts
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- Score confidence per finding
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- Cite sources
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- Provide actionable recommendations
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## Available Agents
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Agents are in `./agents/` directory:
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| Agent | Best For | API Required |
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|-------|----------|--------------|
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| `perplexity-researcher.md` | Current web info, citations | PERPLEXITY_API_KEY |
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| `gemini-researcher.md` | Multi-angle comparison | GEMINI_API_KEY |
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| `openai-researcher.md` | Structured analysis | OPENAI_API_KEY |
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| `claude-researcher.md` | Deep reasoning | Native (Claude Code) |
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## Usage
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### Basic Research
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```
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User: "Research the best ways to maximize Alaska Airlines miles for Japan flights"
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Geoffrey:
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1. Decomposes into sub-queries:
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- Current Alaska redemption rates to Japan
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- Partner airline options (JAL, etc.)
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- Sweet spots and award availability patterns
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- Credit card earning strategies
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- Recent devaluations or changes
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2. Launches 4 agents in parallel
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3. Synthesizes findings with confidence scores
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```
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### Workflow Command
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Use `/conduct-research [topic]` to trigger full parallel research workflow.
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## Output Format
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```markdown
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## Research: [Topic]
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### Context Applied
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- Domain: [travel/shopping/work/etc]
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- User context loaded: [what was loaded from preferences]
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- Dynamic data fetched: [current point balances, etc]
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### Executive Summary
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[2-3 paragraph overview of key findings and main recommendation]
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### Detailed Findings
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#### Sub-topic 1
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Information with citations throughout. For example, "The Westin Rusutsu
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costs 70,000 points peak" ([Point Hacks](url)) and "offers ski-in/ski-out
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access" ([Marriott](url)).
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#### Sub-topic 2
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More information with inline citations...
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### Multimedia Resources
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- [Video: Title](url) - brief description
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- [Podcast: Episode](url) - brief description
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- [TikTok: @user](url) - brief description
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### What I Discovered You Might Not Know
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- Surprising finding 1 that user likely didn't know
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- Surprising finding 2
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- New source or perspective discovered
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### Recommendations
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1. Actionable recommendation specific to user's context
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2. Another action based on their situation
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### Confidence Assessment
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- High confidence: [topics with multiple agreeing sources]
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- Needs verification: [topics with limited sources]
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- Conflicting information: [where sources disagree]
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### All Sources
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Complete list of every URL referenced:
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- [Source Name 1](full-url)
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- [Source Name 2](full-url)
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- [Source Name 3](full-url)
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```
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**Note:** Every factual claim needs an inline citation. The "All Sources" section at the end provides a consolidated reference list.
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## Saving Research Reports
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**ALWAYS save research reports to Google Docs** after completing research.
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### Default Behavior
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1. Create Google Doc in Geoffrey/Research folder
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2. Use appropriate account (hrg for personal, psd for work)
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3. Apply markdown formatting (headers, bold, links)
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4. Return link to user
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### How to Save
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```bash
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cd skills/google-workspace
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bun docs/create_doc.js <account> --title "<Research Topic>" --folder Research --content "<markdown>"
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```
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### Account Selection
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- **hrg** - Personal travel, consulting
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- **psd** - Work-related research
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- **kh** - Personal projects
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### Future: Obsidian Integration
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Will also save to local Obsidian vault (when skill is built).
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## API Configuration
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Keys stored in: `~/Library/Mobile Documents/com~apple~CloudDocs/Geoffrey/secrets/.env`
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```bash
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PERPLEXITY_API_KEY=pplx-...
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GEMINI_API_KEY=...
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OPENAI_API_KEY=sk-...
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# Note: Claude runs natively in Claude Code, no API key needed
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```
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## Performance
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- **Time**: 30 minutes to 3 hours for exhaustive research (not 15-45 seconds)
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- **Depth**: Exhaustive - multiple search pages, follow links, multimedia
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- **Sources**: Discover new sources, not just known lists
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- **Accuracy**: Cross-referenced with confidence scoring, all claims cited
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## Limitations
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- API rate limits may throttle parallel requests
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- Costs accrue per API call
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- Not all agents may have access to same sources
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- Real-time data (stock prices, availability) needs direct API access
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## Future Enhancements
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- Caching frequent research topics
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- Learning which agents are best for which domains
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- Automatic source credibility scoring
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- Research history and versioning
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