Deep Research

Deep Research

Execute a high-intensity research protocol focused on exhaustive discovery, continuous recursive reflection, and high-density analytical reporting. This skill mandates rigorous fact-grounding, quantitative visualization, and strict adherence to structural and length constraints.

📂 Output Path

Final report destination: /mnt/agents/output/report.md

🚀 Research & Discovery Phase (The 10+ Step Loop)

1. Iterative Search: Perform at least 10 search steps to ensure comprehensive coverage across multiple dimensions. Avoid keyword redundancy; ensure each round brings substantial new information.
2. Credibility & Verification: Prioritize authoritative sources (government sites, academic databases, peer-reviewed journals). Never fabricate data. Every statistic and claim must be accurate and traceable.
3. Recursive Reflection: After EACH search round, output a Thinking Process and a Summary.
   • Thinking: Reflect on content found, identify unmet needs, and plan the next specific step.
   • Summary: Concise recap of key findings.
   • Constraint: Both sections must be short and concise.
4. Quantitative Analysis: Prioritize programming tools for calculations. Actively use IPython to generate charts, graphs, and data visualizations; embed these directly into the Markdown.

📝 Report Engineering Standards

1. Structural Logic & Opening

• Conditional TL;DR: Provide a short direct answer at the beginning only if the user's question can be answered in a few sentences.
• Style Adaptation:
  • If a specific style is implied (e.g., story, interview, case narrative), adhere to it.
  • Default: Strict academic report format.
  • Omit generic Introduction/Background sections unless explicitly required.

2. Depth and Analysis (Mode-Based)

• Academic/Survey Mode:
  • Prioritize comprehensive fact-based detail. Include full definitions, formulas, statistical indicators (CI, metrics), and baseline comparisons.
  • Avoid speculative interpretation; ensure all statements are supported by references.
• Lifestyle/Practical Mode:
  • Incorporate observations, human insights, Pros/Cons, and actionable trade-offs.
  • Reflect on implications and explain why certain patterns matter.

3. Length and Paragraph Constraints

• Total Volume: The final report must exceed 10,000 words.
• Paragraph Rules:
  • Each paragraph must be at least 100 words (max 1,000 words).
  • Subsection Rule: Every subsection (e.g., ## 3.1) MUST contain more than one paragraph.
• Natural Transitions: In English writing, avoid rigid patterns like "First, second, third" or "Firstly, secondly, lastly."

4. Mandatory Table Architecture

• Usage: Use tables as the primary structural tool to replace or shorten long prose for comparisons, workflows, or results.
• Centralized Comparison: Aggregate recurring entities, models, or metrics from across different sections into single, coherent comparison tables.
• Source Integration: Do not include a separate "Source" column. Place numeric citations (e.g., [^1^]) directly within the data cells.

⚖️ Formatting & Citation Rules

• Citation Format: Use [^index^] for factual/formal pieces. Max two citations per sentence.
  • Note: Do not use citations for creative/non-formal writing.
• Bolding Strategy:
  • Bold important keywords, critical numbers, major conclusions, and key insights.
  • Avoid redundant bolding: Do not repeatedly bold the same entity within a short span.
• Visuals: Incorporate diagrams, charts, or photographs generated or found during research to support arguments.
• References: Conclude with exactly ~10 high-quality, formatted references linking to authoritative sources.

🛠 Execution Workflow

1. Explore: Conduct a minimum of 10 search rounds with concise recursive reflections.
2. Visualize: Perform IPython-based data analysis and embed generated charts.
3. Write: Generate the article at /mnt/agents/output/report.md following the word count and multi-paragraph subsection rules.