# Research

Conduct preliminary research on a topic and generate research outline.

- Repository: https://github.com/Weizhena/Deep-Research-skills (2463 stars)
- Category: Writing
- License: MIT
- Last updated: 2026-08-23
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add Weizhena/Deep-Research-skills --skill research -g -a claude-code -y`
Codex: `npx skills add Weizhena/Deep-Research-skills --skill research -g -a codex -y`
Cursor: `npx skills add Weizhena/Deep-Research-skills --skill research -g -a cursor -y`
Gemini CLI: `npx skills add Weizhena/Deep-Research-skills --skill research -g -a gemini-cli -y`

## Description

Conduct preliminary research on a topic and generate research outline. For academic research, benchmark research, technology selection, etc.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Research Skill - Preliminary Research

## Trigger
`/research <topic>`

## Workflow

### Step 1: Generate Initial Framework from Model Knowledge
Based on topic, use model's existing knowledge to generate:
- Main research objects/items list in this domain
- Suggested research field framework

Output {step1_output}, use request_user_input to confirm:
- Need to add/remove items?
- Does field framework meet requirements?

### Step 2: Web Search Supplement
Use request_user_input to ask for time range (e.g., last 6 months, since 2024, unlimited).

**Parameter Retrieval**:
- `{topic}`: User input research topic
- `{YYYY-MM-DD}`: Current date
- `{step1_output}`: Complete output from Step 1
- `{time_range}`: User specified time range

**Hard Constraint**: The following prompt must be strictly reproduced, only replacing variables in {xxx}, do not modify structure or wording.

Launch 1 web-search-agent (background), **Prompt Template**:
```python
prompt = f"""## Task
Research topic: {topic}
Current date: {YYYY-MM-DD}

Based on the following initial framework, supplement latest items and recommended research fields.

## Existing Framework
{step1_output}

## Goals
1. Verify if existing items are missing important objects
2. Supplement items based on missing objects
3. Continue searching for {topic} related items within {time_range} and supplement
4. Supplement new fields

## Output Requirements
Return structured results directly (do not write files):

### Supplementary Items
- item_name: Brief explanation (why it should be added)
...

### Recommended Supplementary Fields
- field_name: Field description (why this dimension is needed)
...

### Sources
- [Source1](url1)
- [Source2](url2)
"""
```

**One-shot Example** (assuming researching AI Coding History):
```
## Task
Research topic: AI Coding History
Current date: 2025-12-30

Based on the following initial framework, supplement latest items and recommended research fields.

The rest: https://github.com/Weizhena/Deep-Research-skills/blob/HEAD/skills/research-codex-en/research/SKILL.md