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jilinchenandClaude Opus 4.5 013cc823b6 docs: add real workflow examples from AI Agent Demo research

- Show actual outline.yaml, JSON output, and report
- Keep examples concise and elegant

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

2026-01-07 02:03:28 +08:00

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Deep Research Skill for Claude Code

English | 中文

Inspired by RhinoInsight: Improving Deep Research through Control Mechanisms for Model Behavior and Context

A structured research workflow skill for Claude Code, supporting two-phase research: outline generation (extensible) and deep investigation. Human-in-the-loop design ensures precise control at every stage.

Use Cases

Academic Research: Paper surveys, benchmark reviews, literature analysis
Technical Research: Technology comparison, framework evaluation, tool selection
Market Research: Competitor analysis, industry trends, product comparison
Due Diligence: Company research, investment analysis, risk assessment

Installation

# English version
cp -r skills/research-en ~/.claude/skills/research

# Required: Install agent
cp agents/web-search-agent.md ~/.claude/agents/

Commands

Note

: Use run /research instead of /research directly, as slash commands conflict with built-in commands.

Command	Description
`run /research`	Generate research outline with items and fields
`run /research/add-items`	Add more items to existing outline
`run /research/add-fields`	Add more fields to existing outline
`run /research/deep`	Deep research each item with parallel agents
`run /research/report`	Generate markdown report from JSON results

Workflow & Example

Example: Researching "AI Agent Demo 2025"

Phase 1: Generate Outline

run /research AI Agent Demo 2025

Output: ai-agent-demo/outline.yaml

topic: "AI Agent Demo & Review (2025.9-2025.12)"
items:
  - name: "ChatGPT Agent"
    category: "Browser Agent"
    brief: "OpenAI unified Agent, released July 2025"
  - name: "Claude Computer Use"
    category: "Desktop Agent"
    brief: "Anthropic desktop control Agent"
  # ... 15 more items

Phase 2: Deep Research

run /research/deep

Output: ai-agent-demo/results/ChatGPT_Agent.json

{
  "basic_info": {
    "name": "ChatGPT Agent",
    "company": "OpenAI",
    "release_date": "2025-07-17",
    "pricing": "Pro $200/mo, Plus $20/mo"
  },
  "tech_specs": {
    "underlying_model": "GPT-5 series",
    "agent_type": "Unified autonomous Agent"
  }
}

Phase 3: Generate Report

run /research/report

Output: ai-agent-demo/report.md - Markdown report with TOC and all items

References

RhinoInsight: Improving Deep Research through Control Mechanisms for Model Behavior and Context

License

MIT

2.6 KiB Raw Blame History