mcpbeat

Deep Research

hezaohezao/deep-research

Systematic multi-angle web research methodology.

1k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
117
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/HezaoHezao/poirot --skill deep-research

The instruction itself

17 sections, as written by the author

Deep Research

Overview

Systematic methodology for thorough web research. **Load this skill BEFORE

starting any content generation task** to ensure information from multiple

angles, depths, and sources.

When to Use

Always load when:

  • User asks "what is X", "explain X", "research X", "investigate X"
  • User wants to understand a concept, technology, or topic in depth
  • A single web search would be insufficient to answer properly
  • Before creating presentations, reports, articles, or any content requiring

real-world information

Core Principle

Never generate content based solely on general knowledge. A single search

query is NEVER enough.

Research Methodology

Phase 1: Broad Exploration

Start with broad searches to understand the landscape:

  • Initial Survey: Search for the main topic to understand overall context
  • Identify Dimensions: From initial results, identify key subtopics,

themes, angles needing deeper exploration

  • Map the Territory: Note different perspectives, stakeholders, viewpoints

Phase 2: Deep Dive

For each important dimension identified, conduct targeted research:

  • Specific Queries: Search with precise keywords for each subtopic
  • Multiple Phrasings: Try different keyword combinations
  • Fetch Full Content: Use browse_page to read important sources in full,

not just snippets

  • Follow References: When sources mention other resources, search for those

Phase 3: Diversity & Validation

Ensure comprehensive coverage by seeking diverse information types:

| Information Type | Purpose | Example Searches |

|-----------------|---------|------------------|

| Facts & Data | Concrete evidence | "statistics", "data", "market size" |

| Examples & Cases | Real-world applications | "case study", "example", "implementation" |

| Expert Opinions | Authority perspectives | "expert analysis", "interview", "commentary" |

| Trends & Predictions | Future direction | "trends 2026", "forecast", "future of" |

| Comparisons | Context and alternatives | "vs", "comparison", "alternatives" |

| Challenges & Criticisms | Balanced view | "challenges", "limitations", "criticism" |

Phase 4: Synthesis Check

Before proceeding to content generation, verify:

  • [ ] Searched from at least 3-5 different angles?
  • [ ] Fetched and read the most important sources in full?
  • [ ] Have concrete data, examples, and expert perspectives?
  • [ ] Explored both positive aspects and challenges/limitations?
  • [ ] Information is current and from authoritative sources?

If any answer is NO, continue researching before generating content.

Search Strategy Tips

Effective Query Patterns

# Be specific with context
"enterprise AI adoption trends 2026"

# Include authoritative source hints
"[topic] research paper"
"[topic] McKinsey report"

# Search for specific content types
"[topic] case study"
"[topic] statistics"

# Use temporal qualifiers — use the ACTUAL current year
"[topic] 2026"
"[topic] latest"

Temporal Awareness

Always check the current date before forming search queries:

| User intent | Temporal precision | Example query |

|---|---|---|

| "today / just released" | Month + Day | "tech news February 28 2026" |

| "this week" | Week range | "technology releases week of Feb 24 2026" |

| "recently / latest" | Month | "AI breakthroughs February 2026" |

| "this year / trends" | Year | "software trends 2026" |

When to Use browse_page

Use browse_page to read full content when:

  • A search result looks highly relevant and authoritative
  • You need detailed information beyond the snippet
  • The source contains data, case studies, or expert analysis

Iterative Refinement

Research is iterative:

  • Review what you've learned
  • Identify gaps in your understanding
  • Formulate new, more targeted queries
  • Repeat until comprehensive coverage

Quality Bar

Research is sufficient when you can confidently answer:

  • What are the key facts and data points?
  • What are 2-3 concrete real-world examples?
  • What do experts say about this topic?
  • What are the current trends and future directions?
  • What are the challenges or limitations?
  • What makes this topic relevant or important now?

Common Mistakes

  • ❌ Stopping after 1-2 searches
  • ❌ Relying on search snippets without reading full sources
  • ❌ Searching only one aspect of a multi-faceted topic
  • ❌ Ignoring contradicting viewpoints or challenges
  • ❌ Using outdated information when current data exists
  • ❌ Starting content generation before research is complete

Output

After completing research, you should have:

  • Comprehensive understanding from multiple angles
  • Specific facts, data points, and statistics
  • Real-world examples and case studies
  • Expert perspectives and authoritative sources
  • Current trends and relevant context

Only then proceed to content generation.

How to use it

Copy the folder

Take hezaohezao/deep-research from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.