Add OrbitOS skills (bundled)
- orbites-research: deep research workflow - orbites-parse-knowledge: structure unstructured text - orbites-obsidian-markdown: Obsidian markdown reference - obsidian: vault read/write/search - Updated README: 20 skills total, OrbitOS bundled
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skills/orbitos/orbites-research/SKILL.md
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skills/orbitos/orbites-research/SKILL.md
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name: orbites-research
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description: Deep research workflow for OrbitOS — investigate a topic, create main research note, extract atomic wiki concepts. Use when user says 'research [topic]', 'deep dive', 'study', 'เรียนรู้', 'วิจัย'.
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---
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# OrbitOS: Research — Deep Dive
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You are the Research Coordinator for OrbitOS. Investigate topics and create structured knowledge using a two-agent workflow.
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## Input
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The user provides:
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- A topic (e.g., "React Server Components", "Consistent Hashing")
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- Optional: Specific questions or goals
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- Optional: Related project context
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## Phase 1: Plan (Delegate to Subagent)
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Spawn planning subagent:
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```python
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context = f"""
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Create research plan for: [topic + user context]
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1. Identify context:
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- Check if relates to active project in 20_Project/
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- Determine relevant Area (SoftwareEngineering, Finance, Health, etc.)
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- Search 30_Research/ and 40_Wiki/ for existing content (avoid duplication)
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2. Scan 99_System/Prompts/ for relevant expertise persona
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3. Create plan at 90_Plans/Plan_YYYY-MM-DD_Research_<Topic>.md:
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# Research Plan: [Topic]
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## Research Objective
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[What user will understand]
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## Context Found
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- Related Area: [Area]
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- Existing notes: [list or 'None found']
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- Related project: [project or N/A]
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## Research Strategy
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[ ] Find official docs
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[ ] Find practical examples
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[ ] Identify key concepts for Wiki
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[ ] Find common pitfalls
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## Output Structure
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- Main note: 30_Research/<Area>/<Topic>/<Topic>.md
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- Atomic concepts: 40_Wiki/<Category>/<ConceptName>.md
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- Examples: 30_Research/<Area>/<Topic>/examples/ (if needed)
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4. Return the plan file path.
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"""
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delegate_task(goal="Create research plan", context=context, toolsets=["web", "file"])
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```
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After planning agent returns, ask user: "Research plan at `[path]`. Review and confirm?"
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## Phase 2: Execute (After User Confirmation)
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Spawn execution subagent:
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```python
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context = f"""
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Execute research plan at: 90_Plans/Plan_YYYY-MM-DD_Research_<Topic>.md
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1. Read the plan file
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2. Conduct research:
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- Use web_search and web_extract for current information
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- Gather practical examples
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- Identify atomic concepts to extract
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3. Create main research note at path from plan:
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- Sections: Overview, Key Concepts (with [[wikilinks]]), How It Works, Examples, Best Practices, Common Pitfalls, See Also, Resources
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4. Create atomic wiki notes: 40_Wiki/<Category>/<Concept>.md
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- Keep concise (1-3 paragraphs)
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- Include 'See Also' section
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5. Create examples folder: 30_Research/<Area>/<Topic>/examples/ if needed
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6. Link in today's daily note: 10_Daily/YYYY-MM-DD.md
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7. Archive plan to 90_Plans/Archives/
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Main research frontmatter:
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---
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type: reference
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created: YYYY-MM-DD
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area: "[[AreaName]]"
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tags: [research, topic-tags]
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status: complete
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---
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Wiki note frontmatter:
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---
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area:
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tags: []
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created: YYYY-MM-DD
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---
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"""
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delegate_task(goal="Execute research plan", context=context, toolsets=["web", "terminal", "file"])
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```
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Report back with:
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- **Created:** main note, wiki concepts, examples
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- **Key Takeaways:** 3 main insights
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- **Next Steps:** suggested follow-ups
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## Edge Cases
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- **Topic too broad:** Break into sub-topics
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- **Topic already exists:** Update existing note, don't duplicate
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- **Hands-on topic:** Ensure examples/ folder with working code
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