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:
pythonprompt = 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

