research
Multi-LLM parallel research with query decomposition and synthesis
What this skill does
# Research Skill Discovery-driven, exhaustive research using parallel LLM agents for comprehensive, current information gathering. ## Core Principles **CRITICAL:** These principles define how research works. ### 1. Discovery-Driven, Not List-Driven - Find the BEST sources, not just known sources - Don't limit to predefined source lists - The internet is huge - explore it - Value is in finding what user doesn't already know ### 2. Context-Aware - Load user's domain context from preferences - Research is RELEVANT to their specific situation - But context doesn't limit WHERE you search ### 3. Exhaustive - No time limits - can take 30 minutes to 3 hours - Don't stop at first page of results - Keep going until topic is exhausted - Follow promising links deeper ### 4. Multimedia - Not just text articles - Videos (YouTube), TikTok, podcasts - Real user experiences from forums ### 5. Highly Cited - Every claim must have a citation - Multiple sources for important claims - Note when sources conflict ### 6. Clarifying Questions First Before diving into research, ask deep, thought-provoking questions to understand: - What's the actual goal? (not just the surface request) - What constraints exist? (budget, time, preferences) - What would success look like? - What have they already tried or considered? - Are there hidden requirements? Example: "Research Japan ski trip" should prompt: - "What skill level are you and Carrie? Blue runs, black diamonds?" - "Is après-ski culture important, or pure skiing focus?" - "Do you need English-friendly areas, or comfortable with Japanese-only?" - "Any specific dates that are fixed vs flexible?" - "Besides skiing, anything else you want to do (onsen, food tours)?" ## Domain Context Loading Research automatically loads relevant context from preferences based on detected domain. ### How It Works 1. Detect domain from query (travel, shopping, work, etc.) 2. Load `research_domains.[domain]` from preferences 3. Load referenced context keys 4. Fetch any dynamic data (point balances, etc.) 5. Apply domain-specific research patterns ### Available Domains - **travel** - Loads loyalty programs, credit cards, ski passes, fetches point balances - **work_education** - Loads PSD context, CoSN membership, K-12 patterns - **shopping** - Price comparison, quality patterns - **ai_coding** - Tech stack, GitHub/HN patterns - **consulting** - Strategic recommendations patterns ### Dynamic Data Fetching For travel research, use browser-control to fetch current: - Marriott points balance - Alaska miles balance - Chase points balance - Active transfer bonus promotions ## When to Activate Use this skill when user needs: - Current information (credit card perks, travel deals, policies) - Multi-perspective analysis (comparing options) - Deep investigation of complex topics - Fact-checking or verification - Market research or trend analysis ## Travel Research Requirements **CRITICAL:** Travel research MUST include user-generated content: ### Required Sections for Travel 1. **User Reviews** - TripAdvisor, FlyerTalk, Reddit feedback 2. **"What I Wish I Knew"** - Common mistakes and gotchas 3. **Real Experiences** - Actual trip reports from similar travelers 4. **Restaurant/Hotel Reviews** - With prices and quality feedback 5. **Transportation Tips** - Real user experiences with logistics ### Sources to Search - TripAdvisor reviews and forums - FlyerTalk (for points/miles properties) - Reddit (r/JapanTravel, r/skiing, r/churning, etc.) - Ski forums and trip reports - Points/miles blogs with personal reviews ### Browser Access for Deep Research Use the **browser-control** skill to scrape full threads and reviews that require: - JavaScript rendering (Reddit, modern forums) - Authentication (FlyerTalk, logged-in content) - Dynamic content loading **Prerequisites:** 1. Brave must be running: `cd skills/browser-control && ./scripts/launch-chrome.sh` 2. User must be logged into relevant sites in the Brave Geoffrey profile **Available Scripts** (in `skills/browser-control/scripts/`): ```bash # Navigate and get page content bun navigate.js "https://www.reddit.com/r/JapanTravel/comments/..." # Extract specific content bun extract.js "https://flyertalk.com/forum/thread" ".post-content" --all # Search travel sites directly bun search.js reddit "Hakuba ski resort tips" bun search.js flyertalk "Marriott Bonvoy Japan redemption" # Capture current page without navigating bun capture.js /tmp/screenshot.png ``` **When to Use Browser Control:** - Reddit threads (full comments, not just preview) - FlyerTalk forum posts (complete thread content) - Hotel/airline pages requiring login (availability, points pricing) - Sites that block web scraping but allow browsers ### Research Tool Decision Tree **Start with WebSearch/WebFetch** for: - General facts and information - Blog posts and news articles - Static content that's publicly accessible - Quick lookups **Escalate to browser-control** when: - WebFetch returns truncated/incomplete content (JS-rendered sites) - Need authenticated access (user's Marriott/Alaska account) - Need real-time prices or availability - Forum threads show only previews - Site blocks scraping but allows browsers **Example Flow:** 1. User asks: "What do people say about Westin Rusutsu?" 2. Start with `WebSearch` for blog reviews 3. Find promising Reddit/FlyerTalk threads 4. Use `browser-control` to get full thread content 5. Synthesize findings with citations ## Citation Requirements **CRITICAL:** All research output MUST include citations. ### Inline Citations Every factual claim must link to its source: - "The Westin Rusutsu costs 70,000 points peak ([Point Hacks](url))" - "Shinkansen to Nagano takes 1.5 hours ([Corritrip](url))" ### Source Section Every research report must end with a complete "Sources" section listing all URLs used. ### Why This Matters - User needs to verify information - Information changes frequently (credit card perks, prices) - Establishes credibility - Allows deeper exploration ### No Citation = Don't Include If you can't cite a source for a claim, either: 1. Find a source 2. Mark it as "unverified" 3. Don't include it ## Architecture ### Query Decomposition Break complex questions into 3-7 sub-queries covering different angles: - Factual/definitional - Comparative - Current state - Expert opinions - User experiences - Edge cases ### Parallel Agent Execution Launch multiple researcher agents simultaneously: - **Perplexity** - Best for current web information, citations - **Gemini** - Good for multi-perspective synthesis - **OpenAI** - Strong structured analysis - **Claude** - Deep reasoning, nuanced analysis ### Result Synthesis - Collect all findings - Identify consensus vs conflicts - Score confidence per finding - Cite sources - Provide actionable recommendations ## Available Agents Agents are in `./agents/` directory: | Agent | Best For | API Required | |-------|----------|--------------| | `perplexity-researcher.md` | Current web info, citations | PERPLEXITY_API_KEY | | `gemini-researcher.md` | Multi-angle comparison | GEMINI_API_KEY | | `openai-researcher.md` | Structured analysis | OPENAI_API_KEY | | `claude-researcher.md` | Deep reasoning | Native (Claude Code) | ## Usage ### Basic Research ``` User: "Research the best ways to maximize Alaska Airlines miles for Japan flights" Geoffrey: 1. Decomposes into sub-queries: - Current Alaska redemption rates to Japan - Partner airline options (JAL, etc.) - Sweet spots and award availability patterns - Credit card earning strategies - Recent devaluations or changes 2. Launches 4 agents in parallel 3. Synthesizes findings with confidence scores ``` ### Workflow Command Use `/conduct-research [topic]` to trigger full parallel research workflow. ## Output Format ```markdown ## Research: [Topic] ### Context Applied - Domain: [travel/shopping/work/etc] - User context loaded: [what was loaded from preferences] - Dyn
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