🔬 Research & EvidenceSkill #17

Deep Research Engine

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Place the downloaded SKILL.md into the skills path for your chosen AI assistant:

  • Google Antigravity: <project>/.agents/skills/deep-research-engine/SKILL.md (or global in ~/.gemini/antigravity/skills/deep-research-engine/SKILL.md)
  • Claude Code: ~/.claude/skills/deep-research-engine/SKILL.md
  • Cursor: <project>/.cursor/skills/deep-research-engine/SKILL.md or ~/.cursor/skills/deep-research-engine/SKILL.md
  • Windsurf / VS Code: <project>/.agents/skills/deep-research-engine/SKILL.md
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---
name: deep-research
description: Use when the user needs multi-source research with citation tracking, evidence persistence, and structured report generation. Triggers on "deep research", "comprehensive analysis", "research report", "compare X vs Y", "analyze trends", or "state of the art". Not for simple lookups, debugging, or questions answerable with 1-2 searches.
---

# Deep Research

## Core Purpose

Deliver citation-tracked research reports through a structured pipeline with evidence persistence, source identity management, claim-level verification, and progressive context management.

**Autonomy Principle:** Operate independently. Infer assumptions from context. Only stop for critical errors or incomprehensible queries. Surface high-materiality assumptions explicitly in the Introduction and Methodology rather than silently defaulting.

---

## 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.

---

## Workflow Overview

| Phase | Name | Quick | Std | Deep | Ultra |
|-------|------|-------|-----|------|-------|
| 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 |

**Note:** Phases 3-5 operate as an evidence loop per section (retrieve → evidence store → refine outline → draft → verify claims → delta-retrieve if needed), not as strict sequential gates.

---

## 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: [report_template.md](./templates/report_template.md)
- HTML styling: [mckinsey_report_template.html](./templates/mckinsey_report_template.html)

**Scripts:**
- `python scripts/validate_report.py --report [path]`
- `python scripts/verify_citations.py --report [path]`
- `python scripts/md_to_html.py [markdown_path]`

---

## 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 of truth)
- `sources.jsonl` — stable source registry with canonical IDs
- `evidence.jsonl` — append-only evidence store with quotes and locators
- `claims.jsonl` — atomic claim ledger with support status
- `run_manifest.json` — query, mode, assumptions, provider config
- HTML (McKinsey style, auto-opened)
- PDF (professional print, auto-opened)

**Quality standards:**
- 10+ sources, 3+ per major claim (cluster-independent, not just count)
- All factual claims cited immediately [N] with evidence backing in `evidence.jsonl`
- Claim-support verification mandatory: no unsupported factual claims pass delivery
- No placeholders, no fabricated citations
- Prose-first (>=80%), bullets sparingly

---

## 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.

In Google Antigravity, skills reside in your project workspace under .agents/skills/deep-research-engine/SKILL.md or globally in ~/.gemini/antigravity/skills/.

npx skills add https://github.com/199-biotechnologies/claude-deep-research-skill --skill deep-research-engine -y
# Workspace path: .agents/skills/deep-research-engine/SKILL.md
# Global path: ~/.gemini/antigravity/skills/deep-research-engine/SKILL.md

In Claude Code, install globally using the official skills CLI or add via the Claude Code plugin marketplace.

npx skills add https://github.com/199-biotechnologies/claude-deep-research-skill --skill deep-research-engine -g -y
# Or inside Claude Code session:
/plugin install 199-biotechnologies/claude-deep-research-skill

In Cursor, place the skill folder in .cursor/skills/deep-research-engine/SKILL.md or at the workspace level in .agents/skills/.

npx skills add https://github.com/199-biotechnologies/claude-deep-research-skill --skill deep-research-engine -y
# Or place directly into:
# ~/.cursor/skills/deep-research-engine/SKILL.md

In Windsurf / VS Code, agent skills can be installed targeting the windsurf profile or loaded as project rules.

npx skills add https://github.com/199-biotechnologies/claude-deep-research-skill --skill deep-research-engine -a windsurf -y

🎯 What It Does & How It Works

8-phase pipeline with parallel retrieval, source credibility scoring, critique loop-back, and automated validation scripts. Aggregates Brave, Serper, Exa, Jina, Firecrawl via search-cli.

Core Operational Guidelines & Directives

▸Core Purpose
▸Decision Tree
▸Workflow Overview
▸Execution
📦Sub-Skills & Architecture:

This skill is completely self-contained in SKILL.md. All workflows, constraints, and instructions are directly embedded in this single file, making it immediately usable with 1-click download.

⏱️ When to Use

Investment memos, competitive landscapes, citation-backed reports where hallucination risk is unacceptable.

💡 Context from Repository & Architecture

Modes from Quick to UltraDeep. Persists citations to disk (sources.json) so they survive context compaction. Includes validate_report.py and verify_citations.py.

⚡ Starter Prompt Template

Copy and paste this starter prompt into your AI assistant (Antigravity, Claude, Cursor, ChatGPT) to activate this skill:

Prompt TemplateClick button to copy formatted prompt
Act as an expert using the "Deep Research Engine" agent skill. Follow the specialized guidelines to accomplish the task according to best practices.

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