Deep Research
SkillDev toolsSystematic multi-angle web research methodology.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Deep Research skill
What this skill tells your AI
The instructions your AI receives, as published by hezaohezao/poirot in poirot/backend/agents/skill/builtin_skills/research/deep-research/SKILL.md and read by ahel’s review.
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_pageto 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.
Signals
- GitHub stars
- 220
- Forks
- 19
- Last commit
- Jul 2026
- Hacker News mentions
- 1
Advanced
- Catalog kind
- skill
- Gateway key
deep-research-hezaohezao- Source
- github.com/hezaohezao/poirot