deep-research

Multi-source research synthesis with citation tracking, source verification, and structured reporting across 8-phase methodology. Executes parallel searches and spawns concurrent agents to gather 10+ sources quickly, with credibility scoring and triangulation across sources Generates comprehensive markdown reports with full bibliographies, executive summaries, and detailed findings—each claim immediately cited [N] Produces three output formats automatically: markdown (source), McKinsey-style HTML (opened in browser), and professional PDF Includes anti-hallucination protocols, citation verification scripts, and validation gates to catch fabricated sources and missing bibliography entries Supports four research modes (quick/standard/deep/ultradeep) with auto-continuation for reports exceeding 18,000 words, enabling unlimited report length

INSTALLATION
npx skills add https://github.com/199-biotechnologies/claude-deep-research-skill --skill deep-research
Run in your project or agent environment. Adjust flags if your CLI version differs.

SKILL.md

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.
BrowserAct

Let your agent run on any real-world website

Bypass CAPTCHA & anti-bot for free. Start local, scale to cloud.

Explore BrowserAct Skills →

Stop writing automation&scrapers

Install the CLI. Run your first Skill in 30 seconds. Scale when you're ready.

Start free
free · no credit card