# Research Deep

Read research outline, launch independent agent for each item for deep research.

- Repository: https://github.com/Weizhena/Deep-Research-skills (2463 stars)
- Category: AI and agents
- License: MIT
- Last updated: 2026-08-23
- Runs scripts: no, instructions only

## Install

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

## Description

Read research outline, launch independent agent for each item for deep research. Disable task output.

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

# Research Deep - Deep Research

## Trigger
`/research-deep`

## Workflow

### Step 1: Auto-locate Outline
Find `*/outline.yaml` file in current working directory, read items list, execution config (including items_per_agent).

### Step 2: Resume Check
- Check completed JSON files in output_dir
- Skip completed items

### Step 3: Batch Execution
- Batch by batch_size (need user approval before next batch)
- Each agent handles items_per_agent items
- Launch web-search-agent (background parallel, disable task output)

**Parameter Retrieval**:
- `{topic}`: topic field from outline.yaml
- `{item_name}`: item's name field
- `{item_related_info}`: item's complete yaml content (name + category + description etc.)
- `{output_dir}`: execution.output_dir from outline.yaml (default: ./results)
- `{fields_path}`: absolute path to {topic}/fields.yaml
- `{output_path}`: absolute path to {output_dir}/{item_name_slug}.json (slugify item_name: replace spaces with _, remove special chars)

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

**Prompt Template**:
```python
prompt = f"""## Task
Research {item_related_info}, output structured JSON to {output_path}

## Field Definitions
Read {fields_path} to get all field definitions

## Output Requirements
1. Output JSON according to fields defined in fields.yaml
2. Mark uncertain field values with [uncertain]
3. Add uncertain array at the end of JSON, listing all uncertain field names
4. All field values must be in English

## Output Path
{output_path}

## Validation
After completing JSON output, run validation script to ensure complete field coverage:
python ~/.codex/skills/research/validate_json.py -f {fields_path} -j {output_path}
Task is complete only after validation passes.
"""
```

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