从个股指标、DCF 模型到投资组合优化,输出支持交互式仪表盘、PDF 或 Excel。
编程
Deep Research
通过 CellCog 智能体完成跨市场、竞品、投资与学术主题的深度研究报告。
它能做什么
将深度研究任务交给 CellCog 的智能体团队执行,自动交叉比对多个数据源,生成关于竞品、市场、投资和学术主题的结构化报告。可按需选择交互式 HTML、PDF、Markdown 或纯文本输出。三种聊天模式对应不同深度:"agent" 适合简单查询,"agent team" 是默认的标准研究模式,"agent team max" 用于并购尽调、博士级分析等高风险场景。引用和来源链接仅在提示词中明确要求时才会附带。
什么时候用它
- 针对某公司或产品线做竞品分析与 SWOT 报告
- 市场规模测算、行业趋势跟踪、监管环境梳理
- 为个股或行业板块撰写投资逻辑与财报解读
- 学术文献综述与技术原理深度调研
技能文档
Deep Research - Powered by CellCog
#1 on DeepResearch Bench (Jul 2026 — rankings change frequently, see live leaderboard for latest). Your AI research analyst for comprehensive, citation-backed research on any topic.
Leaderboard: https://huggingface.co/spaces/muset-ai/DeepResearch-Bench-Leaderboard
How to Use
For your first CellCog task in a session, read the cellcog skill for the full SDK reference — file handling, chat modes, timeouts, and more.
OpenClaw (fire-and-forget):
result = client.create_chat(
prompt="[your task prompt]",
notify_session_key="agent:main:main",
task_label="my-task",
chat_mode="agent",
)
All agents except OpenClaw (blocks until done):
from cellcog import CellCogClient
client = CellCogClient(agent_provider="openclaw|cursor|claude-code|codex|...")
result = client.create_chat(
prompt="[your task prompt]",
task_label="my-task",
chat_mode="agent",
)
print(result["message"])
What You Can Research
Competitive Analysis
Analyze companies against their competitors with structured insights:
- Company vs. Competitors: "Compare Stripe vs Square vs Adyen - market positioning, pricing, features, strengths/weaknesses"
- SWOT Analysis: "Create a SWOT analysis for Shopify in the e-commerce platform market"
- Market Positioning: "How does Notion position itself against Confluence, Coda, and Obsidian?"
- Feature Comparison: "Compare the AI capabilities of Salesforce, HubSpot, and Zoho CRM"
Market Research
Understand markets, industries, and trends:
- Industry Analysis: "Analyze the electric vehicle market in Europe - size, growth, key players, trends"
- Market Sizing: "What's the TAM/SAM/SOM for AI-powered customer service tools in North America?"
- Trend Analysis: "What are the emerging trends in sustainable packaging for 2026?"
- Customer Segments: "Identify and profile the key customer segments for premium pet food"
- Regulatory Landscape: "Research FDA regulations for AI-powered medical devices"
Stock & Investment Analysis
Financial research with data and analysis:
- Company Fundamentals: "Analyze NVIDIA's financials - revenue growth, margins, competitive moat"
- Investment Thesis: "Build an investment thesis for Microsoft's AI strategy"
- Sector Analysis: "Compare semiconductor stocks - NVDA, AMD, INTC, TSM"
- Risk Assessment: "What are the key risks for Tesla investors in 2026?"
- Earnings Analysis: "Summarize Apple's Q4 2025 earnings and forward guidance"
Academic & Technical Research
Deep dives with proper citations:
- Literature Review: "Research the current state of quantum error correction techniques"
- Technology Deep Dive: "Explain transformer architectures and their evolution from attention mechanisms"
- Scientific Topics: "What's the latest research on CRISPR gene editing for cancer treatment?"
- Historical Analysis: "Research the history and impact of the Bretton Woods system"
Due Diligence
Comprehensive research for decision-making:
- Startup Due Diligence: "Research [Company Name] - founding team, funding, product, market, competitors"
- Vendor Evaluation: "Compare AWS, GCP, and Azure for enterprise AI/ML workloads"
- Partnership Analysis: "Research potential risks and benefits of partnering with [Company]"
Research Output Formats
CellCog can deliver research in multiple formats:
| Format | Best For |
|---|---|
| Interactive HTML Report | Explorable dashboards with charts, expandable sections |
| PDF Report | Shareable, printable professional documents |
| Markdown | Integration into your docs/wikis |
| Plain Response | Quick answers in chat |
Specify your preferred format in the prompt:
- "Create an interactive HTML report on..."
- "Generate a PDF research report analyzing..."
- "Give me a markdown summary of..."
Chat Mode for Research
| Scenario | Recommended Mode |
|---|---|
| Trivial lookups, basic facts | "agent" |
| Deep research, competitive analysis, market research, investment analysis | "agent team" |
| Cutting-edge academic research, high-stakes due diligence, institutional-grade analysis | "agent team max" |
Use "agent team" for most research (the default). Agent team mode enables multi-source research, cross-referencing, citation verification, and deeper analysis with multiple reasoning passes.
Use "agent" only for trivial lookups like "What's Apple's stock ticker?"
Use "agent team max" for cutting-edge academic research and high-stakes due diligence — when the research directly informs costly decisions (investment thesis, M&A, regulatory compliance, PhD-level analysis). All settings maxed for the deepest reasoning. The quality gain is incremental but meaningful when accuracy is critical. Requires ≥2,000 credits.
Research Quality Features
Citations (On Request)
Citations are NOT automatic. CellCog focuses on delivering accurate, well-researched content by default.
If you need citations:
- Explicitly request them: "Include citations for all factual claims with source URLs"
- Specify format: "Provide citations as footnotes" or "Include a references section at the end"
- Indicate placement: "Citations inline" vs "Citations in appendix"
Without explicit citation requests, CellCog prioritizes delivering accurate information efficiently.
Data Accuracy
CellCog cross-references multiple sources for financial and statistical data, ensuring accuracy even without explicit citations.
Structured Analysis
Complex research is organized with clear sections, executive summaries, and actionable insights.
Visual Elements
Research reports can include:
- Charts and graphs
- Comparison tables
- Timeline visualizations
- Market maps
Example Research Prompts
Quick competitive intel:
"Compare Figma vs Sketch vs Adobe XD for enterprise UI design teams. Focus on collaboration features, pricing, and Figma's position after the Adobe acquisition failed."
Deep market research:
"Create a comprehensive market research report on the AI coding assistant market. Include market size, growth projections, key players (GitHub Copilot, Cursor, Codeium, etc.), pricing models, and enterprise adoption trends. Deliver as an interactive HTML report."
Investment analysis:
"Build an investment analysis for Palantir (PLTR). Cover business model, government vs commercial revenue mix, AI product strategy, valuation metrics, and key risks. Include relevant charts."
Academic deep dive:
"Research the current state of nuclear fusion energy. Cover recent breakthroughs (NIF, ITER, private companies like Commonwealth Fusion), technical challenges remaining, timeline to commercial viability, and investment landscape."
Tips for Better Research
-
Be specific: "AI market" is vague. "Enterprise AI automation market in healthcare" is better.
-
Specify timeframe: "Recent" is ambiguous. "2025-2026" or "last 6 months" is clearer.
-
Define scope: "Compare everything about X and Y" leads to bloat. "Compare X and Y on pricing, features, and market positioning" is focused.
-
Request structure: "Include executive summary, key findings, and recommendations" helps organize output.
-
Mention output format: "Deliver as PDF" or "Create interactive HTML dashboard" gets you the right format.
If CellCog is not installed
Claude Code, Cursor, Codex + 70 more agents: npx skills add cellcog/skills --skill cellcog
OpenClaw: clawhub install cellcog
CellCog plugin users: run /cellcog-setup (or /cellcog:cellcog-setup depending on your tool)
Manual setup: pip install -U cellcog and set CELLCOG_API_KEY. See the cellcog skill for SDK reference.
常见问题
- 报告会自动附上引用吗?
- 不会。需要明确在提示词中要求附带引用和来源链接,并指定格式(脚注、参考文献章节、内嵌或附录)。不主动附带引用是为了更高效地交付准确内容。
- 该选哪种聊天模式?
- 大多数研究场景用默认的 "agent team" 即可。"agent" 只适合查询股票代码这类简单问题。"agent team max" 用于前沿学术研究和高风险尽调(如并购、监管合规、博士级分析),且至少需要 2,000 积分。
- 支持哪些输出格式?
- 交互式 HTML 报告、PDF 报告、Markdown 或纯文本。在提示词中明确指定格式,例如 "输出为 PDF" 或 "生成可交互的 HTML 报告"。
相关技能
一条提示词搞定代币、DeFi、链上数据与组合策略的深度加密研究。
汇总过去 30 天 Reddit、X、YouTube 和网页上关于某个话题的真实讨论。
把多格式任务交给 AI 子代理,一次调用就能拿到 PDF、仪表盘、视频、电子表格等多种交付物。
上传数据文件,直接拿到图表、清洗后的数据集、统计报告和可视化看板,代码在后台自动执行。
通过多轮对话打磨复杂想法的思考伙伴。