Agent skill

research-and-incorporate

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.

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Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/research-and-incorporate

Metadata

Additional technical details for this skill

source
Chesterton's Fence research workflow (Session 203)
timelessness
8/10

SKILL.md

Research and Incorporate

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

Quick Start

text
/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

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

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