Skill: litiao1224/deep-research-pro-litiao (version 1.0.0)

--- name: deep-research-pro-litiao version: 1.1.0 description: "Multi-source deep research agent. Searches the web, synthesizes findings, and delivers cited reports. Uses Tavily API (preferred) or DuckDuckGo (fallback)." homepage: https://github.com/paragshah/deep-research-pro metadata: {"clawdbot":{"emoji":"🔬","category":"research","requires":{"env":["TAVILY_API_KEY"]}}} --- # Deep Research Pro 🔬 A powerful, self-contained deep research skill that produces thorough, cited reports from multiple web sources. **Prefers Tavily API** for cleaner, AI-optimized results — falls back to DuckDuckGo if API key unavailable. ## How It Works When the user asks for research on any topic, follow this workflow: ### Step 1: Understand the Goal (30 seconds) Ask 1-2 quick clarifying questions: - "What's your goal — learning, making a decision, or writing something?" - "Any specific angle or depth you want?" If the user says "just research it" — skip ahead with reasonable defaults. ### Step 2: Plan the Research (think before searching) Break the topic into 3-5 research sub-questions. For example: - Topic: "Impact of AI on healthcare" - What are the main AI applications in healthcare today? - What clinical outcomes have been measured? - What are the regulatory challenges? - What companies are leading this space? - What's the market size and growth trajectory? ### Step 3: Execute Multi-Source Search **Preferred: Use Tavily Search** (if `TAVILY_API_KEY` is available): ```bash # General web search cd ~/.openclaw/workspace/skills/tavily-search-litiao node scripts/search.mjs "<sub-question keywords>" -n 10 # News search (for current events) node scripts/search.mjs "<topic>" --topic news --days 3 # Deep search (for complex topics) node scripts/search.mjs "<complex query>" --deep ``` **Fallback: DuckDuckGo** (if Tavily unavailable): ```bash # Web search /home/clawdbot/clawd/skills/ddg-search/scripts/ddg "<sub-question keywords>" --max 8 # News search (for current events) /home/clawdbot/clawd/skills/ddg-search/scripts/ddg news "<topic>" --max 5 ``` **Search strategy:** - Use 2-3 different keyword variations per sub-question - Mix web + news searches - Aim for 15-30 unique sources total - Prioritize: academic, official, reputable news > blogs > forums - **Tavily advantage**: Returns cleaner snippets, better for AI synthesis ### Step 4: Deep-Read Key Sources For the most promising URLs, fetch full content: ```bash curl -sL "<url>" | python3 -c " import sys, re html = sys.stdin.read() # Strip tags, get text text = re.sub('<[^>]+>', ' ', html) text = re.sub(r'\s+', ' ', text).strip() print(text[:5000]) " ``` Read 3-5 key sources in full for depth. Don't just rely on search snippets. ### Step 5: Synthesize & Write Report Structure the report as: ```markdown # [Topic]: Deep Research Report *Generated: [date] | Sources: [N] | Confidence: [High/Medium/Low]* ## Executive Summary [3-5 sentence overview of key findings] ## 1. [First Major Theme] [Findings with inline citations] - Key point ([Source Name](url)) - Supporting data ([Source Name](url)) ## 2. [Second Major Theme] ... ## 3. [Third Major Theme] ... ## Key Takeaways - [Actionable insight 1] - [Actionable insight 2] - [Actionable insight 3] ## Sources 1. [Title](url) — [one-line summary] 2. ... ## Methodology Searched [N] queries across web and news. Analyzed [M] sources. Sub-questions investigated: [list] ``` ### Step 6: Save & Deliver Save the full report: ```bash mkdir -p ~/clawd/research/[slug] # Write report to ~/clawd/research/[slug]/report.md ``` Then deliver: - **Short topics**: Post the full report in chat - **Long reports**: Post the executive summary + key takeaways, offer full report as file ## Quality Rules 1. **Every claim needs a source.** No unsourced assertions. 2. **Cross-reference.** If only one source says it, flag it as unverified. 3. **Recency matters.** Prefer sources from the last 12 months. 4. **Acknowledge gaps.** If you couldn't find good info on a sub-question, say so. 5. **No hallucination.** If you don't know, say "insufficient data found." ## Examples ``` "Research the current state of nuclear fusion energy" "Deep dive into Rust vs Go for backend services in 2026" "Research the best strategies for bootstrapping a SaaS business" "What's happening with the US housing market right now?" ``` ## For Sub-Agent Usage When spawning as a sub-agent, include the full research request and context: ``` sessions_spawn( task: "Run deep research on [TOPIC]. Follow the deep-research-pro SKILL.md workflow. Read /home/clawdbot/clawd/skills/deep-research-pro/SKILL.md first. Goal: [user's goal] Specific angles: [any specifics] Save report to ~/clawd/research/[slug]/report.md When done, wake the main session with key findings.", label: "research-[slug]", model: "opus" ) ``` ## Requirements **Preferred:** - Tavily API key: `TAVILY_API_KEY` (get from https://tavily.com) - Tavily scripts: `~/.openclaw/workspace/skills/tavily-search-litiao/scripts/` **Fallback (no API key needed):** - DDG search script: `/home/clawdbot/clawd/skills/ddg-search/scripts/ddg` **Both methods:** - curl (for fetching full pages)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)