Skill: marjoriebroad/abe-deep-research-pro (version 1.0.0)

--- name: deep-research-pro version: 1.0.0 description: "Multi-source deep research agent. Searches the web via SkillBoss API Hub, synthesizes findings, and delivers cited reports." homepage: https://github.com/paragshah/deep-research-pro metadata: {"clawdbot":{"emoji":"🔬","category":"research"}} requires.env: [SKILLBOSS_API_KEY] --- # Deep Research Pro 🔬 A powerful, self-contained deep research skill that produces thorough, cited reports from multiple web sources. Powered by SkillBoss API Hub — web search and page scraping via a single unified API. ## 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 For EACH sub-question, call SkillBoss API Hub search: ```python import requests, os SKILLBOSS_API_KEY = os.environ["SKILLBOSS_API_KEY"] # Web search result = requests.post( "https://api.heybossai.com/v1/pilot", headers={"Authorization": f"Bearer {SKILLBOSS_API_KEY}", "Content-Type": "application/json"}, json={"type": "search", "inputs": {"query": "<sub-question keywords>"}, "prefer": "balanced"}, timeout=60 ).json() search_results = result["result"]["results"] # News search (for current events) result = requests.post( "https://api.heybossai.com/v1/pilot", headers={"Authorization": f"Bearer {SKILLBOSS_API_KEY}", "Content-Type": "application/json"}, json={"type": "search", "inputs": {"query": "<topic>", "search_type": "news"}, "prefer": "balanced"}, timeout=60 ).json() news_results = result["result"]["results"] ``` **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 ### Step 4: Deep-Read Key Sources For the most promising URLs, fetch full content via SkillBoss API Hub scraping: ```python result = requests.post( "https://api.heybossai.com/v1/pilot", headers={"Authorization": f"Bearer {SKILLBOSS_API_KEY}", "Content-Type": "application/json"}, json={"type": "scraping", "inputs": {"url": "<url>"}}, timeout=60 ).json() content = result["result"]["results"] ``` 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 - `SKILLBOSS_API_KEY` environment variable (for web search and page scraping via SkillBoss API Hub) - Python 3.11+ with `requests` library


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