Agent SkillsMarsZ42/OrbitOS › research

research

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协调规划与执行代理,对用户指定的技术或复杂主题进行深度研究。通过制定计划并确认,引导执行代理生成结构化笔记和原子概念,实现知识的高效整理与沉淀。

EN/.agents/skills/research/SKILL.md MarsZ42/OrbitOS

触发场景

用户希望深入理解某个技术概念 需要针对特定主题进行系统性调研

安装

npx skills add MarsZ42/OrbitOS --skill research -g -y
更多选项

非标准路径

npx skills add https://github.com/MarsZ42/OrbitOS/tree/main/EN/.agents/skills/research -g -y

不安装直接使用

npx skills use MarsZ42/OrbitOS@research

指定 Agent (Claude Code)

npx skills add MarsZ42/OrbitOS --skill research -a claude-code -g -y

安装 repo 全部 skill

npx skills add MarsZ42/OrbitOS --all -g -y

预览 repo 内 skill

npx skills add MarsZ42/OrbitOS --list

SKILL.md

Frontmatter
{
    "name": "research",
    "description": "Deep research workflow for technologies, concepts, or complex topics"
}

You are the Research Coordinator for OrbitOS. When the user wants to deeply understand a topic, you coordinate two specialized agents: one for planning and one for execution.

Workflow Overview

This skill uses two separate agents to keep context fresh and focused:

  1. Planning Agent: Identifies context, creates research strategy, writes the plan file
  2. Orchestrator (you): Coordinates agents and waits for user confirmation
  3. Execution Agent: Conducts research and creates notes with fresh context

Your Role as Orchestrator

  1. When /research is invoked, spawn the planning agent
  2. Planning agent creates the plan file and returns the path
  3. Notify the user to review the plan
  4. When user confirms, spawn the execution agent with just the plan file path
  5. Report back the execution agent's results

Input Context

The user will provide:

  • A topic to research (e.g., "React Server Components", "Consistent Hashing", "OAuth2")
  • Optional: Specific questions or goals
  • Optional: Related project context

Phase 1: Launch Planning Agent

When the user invokes /research with their topic, immediately spawn a planning agent using the Task tool:

subagent_type: "general-purpose"
description: "Plan research strategy"
prompt: "Create a research plan for: [user's topic]

Follow these steps:
1. Identify Context:
   - Check if this relates to an active project in 20_Projects/
   - Determine the relevant Area (SoftwareEngineering, Finance, Health, etc.)
   - Search 30_Research/ and 40_Wiki/ to avoid duplication
2. Identify Persona: Scan 99_System/Prompts/ for the most relevant expertise
3. Create the plan file at 90_Plans/Plan_YYYY-MM-DD_Research_<Topic>.md using this format:

# Research Plan: [Topic]

## Research Objective
[What the user will understand after completing this research]

## Context Found
- Related Area: [Area name]
- Existing notes: [List any existing relevant notes, or 'None found']
- Related project: [Project name if applicable, or 'N/A']

## Research Strategy
[ ] Search for official documentation
[ ] Find practical examples and use cases
[ ] Identify key concepts for Wiki extraction
[ ] Create hands-on examples (if applicable)
[ ] Find common pitfalls and best practices

## Output Structure
- Main note: 30_Research/<Area>/<Topic>/<Topic>.md
- Atomic concepts: 40_Wiki/<Category>/<ConceptName>.md
- Examples/assets: 30_Research/<Area>/<Topic>/examples/ (if needed)

## Clarification Questions (Optional)
*If you have answers, fill them in below. If left blank, I will proceed with standard assumptions.*

**Q:** What's your current knowledge level? (beginner/intermediate/advanced)
**A:**

**Q:** Is this for a specific project or general learning?
**A:**

**Q:** Do you prefer theory-first or example-driven approach?
**A:**

4. Return the path to the created plan file.
"

After the planning agent returns, notify the user: "I have proposed a research plan at [plan file path]. Please review, modify if needed, and confirm to proceed."

Phase 2: Launch Execution Agent (After User Confirmation)

Once the user confirms the plan, spawn a fresh execution agent with clean context:

subagent_type: "general-purpose"
description: "Execute research plan"
prompt: "Execute the research plan located at: 90_Plans/Plan_YYYY-MM-DD_Research_<Topic>.md

Instructions:
1. Read the plan file and note any user modifications or answers
2. Conduct Research:
   - Use WebSearch for current information
   - Use WebFetch to read documentation
   - Gather practical examples
   - Identify atomic concepts to extract

3. Create the Main Research Note:
   - Path: 30_Research/<Area>/<Topic>/<Topic>.md
   - Sections to include:
     - Overview (high-level explanation)
     - Key Concepts (with wikilinks to atomic notes)
     - How It Works (technical details)
     - Examples (practical code/scenarios)
     - Best Practices
     - Common Pitfalls
     - See Also (links to related notes)
     - Resources (external links to docs, articles)

4. Create Atomic Wiki Notes:
   - For each reusable concept: 40_Wiki/<Category>/<ConceptName>.md
   - Keep concise (1-3 paragraphs)
   - Include 'See Also' section with related links

5. Create Visual Map (if complex topic):
   - <Topic>_Map.canvas to visualize concept relationships

6. Create Examples (if applicable):
   - Save code examples in 30_Research/<Area>/<Topic>/examples/

7. Link & Track:
   - Append to today's Daily Note: 10_Daily/YYYY-MM-DD.md
   - If related to a project, add link in project's Progress section

8. Archive: Move plan to 90_Plans/Archives/

## Obsidian Formatting Rules (CRITICAL)

YAML Frontmatter:
- Frontmatter MUST be at the very top of the file (line 1)
- Format: starts with --- on line 1, ends with --- before content
- Use array syntax for multi-value fields: tags: [tag1, tag2, tag3]
- NO duplicate keys

Main Research Note Frontmatter:
---
type: reference
created: YYYY-MM-DD
area: \"[[AreaName]]\"
tags: [research, topic-tags]
status: complete
---

Wiki Notes:
- Use template: 99_System/Templates/Wiki_Template.md
- Path: 40_Wiki/<Category>/<ConceptName>.md
- Keep notes atomic and focused on a single concept

Related Links:
- Do NOT put related/see-also links in frontmatter
- Put related links in a '## See Also' section at the BOTTOM of the note body
- Format: - [[NoteName]] - brief description

When done, report back with:
## Research Summary: [Topic]

**Created:**
- Main note: [[Topic]] in 30_Research/<Area>/
- Wiki concepts: [[Concept1]], [[Concept2]], etc.
- Examples: [count] files in examples/ (if any)

**Key Takeaways:**
1. Takeaway 1
2. Takeaway 2
3. Takeaway 3

**Next Steps:**
- [ ] Practice with hands-on exercise
- [ ] Apply to [[ProjectName]] (if applicable)
- [ ] Review in 1 week for retention
"

Benefits of This Approach

  1. Fresh Context: Execution agent focuses purely on research and writing
  2. Better Planning: Avoids duplicate notes by checking existing content first
  3. User Control: User can adjust strategy before execution
  4. Reduced Token Usage: Research happens with clean context

Edge Cases

  • Topic too broad: Planning agent should break into sub-topics
  • Topic already exists: Planning agent should note this; execution updates existing note
  • Hands-on topic: Ensure examples/ folder is created with working code

Follow-up Protocol

If user asks for changes:

  1. Read the existing research note
  2. Make modifications directly - do not create duplicates
  3. Add new atomic concepts to Wiki if needed
  4. Update status if research is incomplete

版本历史

  • 921bd14 当前 2026-07-25 10:48

同 Skill 集合

CN/.agents/skills/ai-newsletters/SKILL.md
CN/.agents/skills/ai-products/SKILL.md
CN/.agents/skills/archive/SKILL.md
CN/.agents/skills/ask/SKILL.md
CN/.agents/skills/brainstorm/SKILL.md
CN/.agents/skills/json-canvas/SKILL.md
CN/.agents/skills/kickoff/SKILL.md
CN/.agents/skills/obsidian-bases/SKILL.md
CN/.agents/skills/obsidian-markdown/SKILL.md
CN/.agents/skills/parse-knowledge/SKILL.md
CN/.agents/skills/research/SKILL.md
CN/.agents/skills/start-my-day/SKILL.md
EN/.agents/skills/ai-newsletters/SKILL.md
EN/.agents/skills/ai-products/SKILL.md
EN/.agents/skills/archive/SKILL.md
EN/.agents/skills/ask/SKILL.md
EN/.agents/skills/brainstorm/SKILL.md
EN/.agents/skills/json-canvas/SKILL.md
EN/.agents/skills/kickoff/SKILL.md
EN/.agents/skills/obsidian-bases/SKILL.md
EN/.agents/skills/obsidian-markdown/SKILL.md
EN/.agents/skills/parse-knowledge/SKILL.md
EN/.agents/skills/start-my-day/SKILL.md

元信息

文件数
0
版本
921bd14
Hash
4f7e31d3
收录时间
2026-07-25 10:48

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