research-and-incorporate

Research

Research external topics, create comprehensive analysis, determine project applicability, and incorporate learnings into Serena and Forgetful memory systems. Transforms knowledge into searchable, actionable project context.

QUICK START

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I want to install this Agent Skill for this project in Codex.

Source SKILL.md: https://github.com/majiayu000/claude-skill-registry/blob/HEAD/skills/analysis/research-and-incorporate-rjmurillo-ai-agents-6eda0be0/SKILL.md

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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

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

Workflow Overview

┌─────────────────────────────────────────────────────────────────┐
│ 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

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