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Szpitale-graph/skills/research-en/deep/SKILL.md
T
jilinchenandClaude Opus 4.5 46529e4b88 feat: support direct slash command trigger (Claude Code 2.1.0+)
- Add user-invocable: true to all SKILL.md files (10 files)
- Update README with new command format (/research:deep)
- Keep backward compatibility notes for older versions

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-08 10:55:57 +08:00

3.4 KiB

user-invocable, description, allowed-tools
user-invocable description allowed-tools
true Read research outline, launch independent agent for each item for deep research. Disable task output. Bash, Read, Write, Glob, WebSearch, Task

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:

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