deep-research-deep

<!-- ===== Layer 1: 永久缓存 ===== --> # 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 ~/.claude/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 /home/weizhena/AIcoding/aicoding-history/results/GitHub_Copilot.json ## Field Definitions Read /home/weizhena/AIcoding/aicoding-history/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 /home/weizhena/AIcoding/aicoding-history/results/GitHub_Copilot.json ## Validation After completing JSON output, run validation script to ensure complete field coverage: python ~/.claude/skills/research/validate_json.py -f /home/weizhena/AIcoding/aicoding-history/fields.yaml -j /home/weizhena/AIcoding/aicoding-history/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