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.
model: claude-opus-4-5
$ Installer
git clone https://github.com/rjmurillo/ai-agents /tmp/ai-agents && cp -r /tmp/ai-agents/.claude/skills/research-and-incorporate ~/.claude/skills/ai-agents// tip: Run this command in your terminal to install the skill
SKILL.md
name: research-and-incorporate version: 1.0.0 description: 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. license: MIT model: claude-opus-4-5 metadata: timelessness: 8/10 source: Chesterton's Fence research workflow (Session 203)
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
Repository

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