Deep Research

Deep Research

Core Purpose

Deliver citation-backed, verified research reports through a structured pipeline with source credibility scoring, evidence persistence, and progressive context management.

Autonomy Principle: Operate independently. Infer assumptions from context. Only stop for critical errors or incomprehensible queries.

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Decision Tree

Request Analysis
+-- Simple lookup? --> STOP: Use WebSearch
+-- Debugging? --> STOP: Use standard tools
+-- Complex analysis needed? --> CONTINUE

Mode Selection
+-- Initial exploration --> quick (3 phases, 2-5 min)
+-- Standard research --> standard (6 phases, 5-10 min) [DEFAULT]
+-- Critical decision --> deep (8 phases, 10-20 min)
+-- Comprehensive review --> ultradeep (8+ phases, 20-45 min)

Default assumptions: Technical query = technical audience. Comparison = balanced perspective. Trend = recent 1-2 years.

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Workflow Overview

| Phase | Name | Quick | Standard | Deep | UltraDeep | |-------|------|-------|----------|------|-----------| | 1 | SCOPE | Y | Y | Y | Y | | 2 | PLAN | - | Y | Y | Y | | 3 | RETRIEVE | Y | Y | Y | Y | | 4 | TRIANGULATE | - | Y | Y | Y | | 4.5 | OUTLINE REFINEMENT | - | Y | Y | Y | | 5 | SYNTHESIZE | - | Y | Y | Y | | 6 | CRITIQUE | - | - | Y | Y | | 7 | REFINE | - | - | Y | Y | | 8 | PACKAGE | Y | Y | Y | Y |

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Execution

On invocation, load relevant reference files:

1. Phase 1-7: Load [methodology.md](./reference/methodology.md) for detailed phase instructions
2. Phase 8 (Report): Load [report-assembly.md](./reference/report-assembly.md) for progressive generation
3. HTML/PDF output: Load [html-generation.md](./reference/html-generation.md)
4. Quality checks: Load [quality-gates.md](./reference/quality-gates.md)
5. Long reports (>18K words): Load [continuation.md](./reference/continuation.md)

Templates:

• Report structure: [reporttemplate.md](./templates/reporttemplate.md)
• HTML styling: [mckinseyreporttemplate.html](./templates/mckinseyreporttemplate.html)

Scripts:

• python scripts/validate_report.py --report [path]
• python scripts/verify_citations.py --report [path]
• python scripts/md_to_html.py [markdown_path]

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Output Contract

Required sections:

• Executive Summary (200-400 words)
• Introduction (scope, methodology, assumptions)
• Main Analysis (4-8 findings, 600-2,000 words each, cited)
• Synthesis & Insights (patterns, implications)
• Limitations & Caveats
• Recommendations
• Bibliography (COMPLETE - every citation, no placeholders)
• Methodology Appendix

Output files (all to ~/Documents/[Topic]_Research_[YYYYMMDD]/):

• Markdown (primary source)
• HTML (McKinsey style, auto-opened)
• PDF (professional print, auto-opened)

Quality standards:

• 10+ sources, 3+ per major claim
• All claims cited immediately [N]
• No placeholders, no fabricated citations
• Prose-first (>=80%), bullets sparingly

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When to Use / NOT Use

Use: Comprehensive analysis, technology comparisons, state-of-the-art reviews, multi-perspective investigation, market analysis.

Do NOT use: Simple lookups, debugging, 1-2 search answers, quick time-sensitive queries.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: mega-edo
• Source: mega-edo/mega-tron
• License: Apache-2.0
• Homepage: https://www.megacode.ai

Install and usage instructions live in the source repository linked above.