research-and-incorporate

Research and Incorporate

Transform external knowledge into actionable, searchable project context through structured research, analysis, and memory integration.

Quick Start

/research-and-incorporate

Topic: Chesterton's Fence
Context: Decision-making principle for understanding existing systems before changing them
URLs: https://fs.blog/chestertons-fence/, https://en.wikipedia.org/wiki/G._K._Chesterton

Input	Output	Duration
Topic + Context + URLs	Analysis doc + Serena memory + 5-10 Forgetful memories	20-40 min

Triggers

• /research-and-incorporate - Main invocation
• research and incorporate {topic} - Natural language
• study {topic} and add to memory - Alternative phrasing
• deep dive on {topic} - Research focus
• learn about {topic} for the project - Project integration focus

When to Use

Use this skill when:

• Researching an external concept, framework, or principle for project integration
• You need structured analysis with memory persistence (not just a web search)
• Building actionable knowledge from external sources

Use memory-documentary instead when:

• Investigating patterns already in existing memory systems
• You need cross-system evidence synthesis, not new external research

Parameters

Parameter	Required	Description
TOPIC	Yes	Subject to research (e.g., "Chesterton's Fence")
CONTEXT	Yes	Why this matters to the project
URLS	No	Comma-separated source URLs

Process

┌─────────────────────────────────────────────────────────────────┐
│ Phase 1: RESEARCH (BLOCKING)                                    │
│ • Check existing knowledge (Serena + Forgetful)                 │
│ • Fetch URLs with quote extraction                              │
│ • Web search for additional context                             │
│ • Synthesize: principles, frameworks, examples, failure modes   │
├─────────────────────────────────────────────────────────────────┤
│ Phase 2: ANALYSIS DOCUMENT (BLOCKING)                           │
│ • Write 3000-5000 word analysis to .agents/analysis/            │
│ • Include: concepts, frameworks, applications, failure modes    │
│ • Verify: 3+ examples, 3+ failure modes, 2+ relationships       │
├─────────────────────────────────────────────────────────────────┤
│ Phase 3: APPLICABILITY (BLOCKING)                               │
│ • Map integration points: agents, protocols, memory, skills     │
│ • Propose applications with effort estimates                    │
│ • Prioritize: High/Medium/Low based on project goals            │
├─────────────────────────────────────────────────────────────────┤
│ Phase 4: MEMORY INTEGRATION (BLOCKING)                          │
│ • Create Serena project memory with cross-references            │
│ • Create 5-10 atomic Forgetful memories (importance 7-10)       │
│ • Link memories to related concepts (auto + manual)             │
├─────────────────────────────────────────────────────────────────┤
│ Phase 5: ACTION ITEMS                                           │
│ • Create GitHub issue if implementation work identified         │
│ • Document in session log                                       │
└─────────────────────────────────────────────────────────────────┘

Quality Gates (BLOCKING)

Gate	Requirement	Phase
Research depth	Core principles + frameworks + 3 examples	1
Analysis length	3000-5000 words minimum	2
Concrete examples	3+ with context and outcomes	2
Failure modes	3+ anti-patterns with corrections	2
Relationships	2+ connections to existing concepts	2
Memory atomicity	Each memory <2000 chars, ONE concept	4
Memory count	5-10 Forgetful memories created	4

Verification Checklist

After completion, verify:

• Analysis document exists at .agents/analysis/{topic-slug}.md
• Analysis is 3000-5000 words with concrete examples
• Applicability section documents integration opportunities
• Serena memory created with cross-references
• 5-10 Forgetful memories created (importance 7-10)
• Memories linked to related concepts
• Each memory is atomic (<2000 chars, one concept)
• Action items documented (issue or next steps)

Anti-Patterns

Avoid	Why	Instead
Superficial research	Surface definitions miss actionable insights	Dig into frameworks, examples, failure modes
Missing applicability	Research without integration is wasted	Every insight must show HOW it applies
Non-atomic memories	>2000 chars or multiple concepts pollutes graph	ONE concept per memory
Disconnected knowledge	Orphaned artifacts aren't discoverable	Link memories to related concepts
Template over-compliance	Forcing irrelevant sections wastes tokens	Organize for the topic, not the template
Skipping verification	Quality gates exist for a reason	Verify each phase before proceeding

Related Skills

Skill	Relationship
using-forgetful-memory	Memory creation best practices
encode-repo-serena	Similar but for codebase analysis
exploring-knowledge-graph	Navigate created knowledge
memory	Search and retrieve incorporated knowledge

References

Document	Content
workflow.md	Detailed phase workflows with templates
memory-templates.md	Forgetful memory structure templates

Extension Points

1. Additional research sources: Add MCP tools for specialized domains
2. Custom analysis templates: Topic-specific document structures
3. Automated validation: Scripts to verify memory atomicity
4. Integration hooks: Connect to ADR review for architecture topics