About research-deep
research-deep is a skill for running structured, batch-based research from an outline.yaml file. It resumes by skipping completed outputs, launches web-search-agent work in parallel, and reports completion and uncertain or failed items.
Key features
- 01Load research items from outline.yaml
- 02Resume by skipping completed outputs
- 03Run work in user-approved batches
- 04Delegate items to parallel web-search-agent tasks
- 05Report completion and uncertain items
Use cases
- 01Conduct structured research across an outline
- 02Resume an interrupted research run
- 03Review results and failures after batch execution
Install
Copy the command and run it in a terminal.
$
npx skills add https:/ / github.com/ weizhena/ deep-research-skills --skill research-deepAfter installing, type/research-deepin Claude Code to confirm it loaded.
Details
From the project READMEResearch 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:
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.
"""
One-shot Example (assuming researching GitHub Copilot):
## Task
Research name: GitHub Copilot
category: International Product
description: Developed by Microsoft/GitHub, first mainstream AI coding assistant, ~40% market share, output structured JSON to {project_dir}/results/GitHub_Copilot.json
## Field Definitions
Read {project_dir}/fields.yaml 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
{project_dir}/results/GitHub_Copilot.json
## Validation
After completing JSON output, run validation script to ensure complete field coverage:
python ~/.codex/skills/research/validate_json.py -f {project_dir}/fields.yaml -j {project_dir}/results/GitHub_Copilot.json
Task is complete only after validation passes.
Step 4: Wait and Monitor
- Wait for current batch to complete
- Launch next batch
- Display progress
Step 5: Summary Report
After all complete, output:
- Completion count
- Failed/uncertain marked items
- Output directory
Agent Config
- Background execution: Yes
- Task Output: Disabled (agent has explicit output file when complete)
- Resume support: Yes
Comments
Markdown supported