Prompt Pattern Library

Customization

Before executing, check for user customizations at: ~/.claude/LIFEOS/USER/CUSTOMIZATIONS/SKILLS/Fabric/

If this directory exists, load and apply any PREFERENCES.md, configurations, or resources found there. These override default behavior. If the directory does not exist, proceed with skill defaults.

Voice Notification

When executing a workflow, do BOTH:

1. Send voice notification:

   curl -s -X POST http://localhost:31337/notify \
     -H "Content-Type: application/json" \
     -d '{"message": "Running the WORKFLOWNAME workflow in the Fabric skill to ACTION"}' \
     > /dev/null 2>&1 &
   

2. Output text notification:

   Running the **WorkflowName** workflow in the **Fabric** skill to ACTION...
   

Full documentation: ~/.claude/LIFEOS/DOCUMENTATION/Notifications/NotificationSystem.md

Fabric

What It Does

Runs any of 240+ specialized prompt patterns across extraction, summarization, analysis, creation, improvement, security, and rating. Common ones: extract_wisdom, create_threat_model, analyze_claims, improve_writing, review_code, mermaid, youtube_summary. Patterns run natively — LifeOS reads the pattern's system.md and applies it directly, no CLI round-trip. The fabric CLI is only used for YouTube transcripts (-y) and URL fallback (-u).

The Problem

Good prompts are scattered, hard to remember, and easy to rewrite badly from scratch each time. You want a threat model, a claims analysis, or a clean summary, but reconstructing the right prompt every time is slow and inconsistent. Calling an external CLI for each one adds latency and a dependency. This skill keeps 240+ proven patterns on hand and applies them directly as prompts, so the right structured prompt is one pattern name away.

How It Works

A prompt pattern system providing 240+ specialized patterns for content analysis, extraction, summarization, threat modeling, and transformation.

Patterns Location: Patterns/

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Workflow Routing

Workflow	Trigger	File
ExecutePattern	"use fabric", "run pattern", "apply pattern", "extract wisdom", "summarize", "analyze with fabric"	Workflows/ExecutePattern.md
UpdatePatterns	"update fabric", "update patterns", "sync fabric", "pull patterns"	Workflows/UpdatePatterns.md

---

Examples

Example 1: Extract wisdom from content

User: "Use fabric to extract wisdom from this article"
-> Invokes ExecutePattern workflow
-> Selects extract_wisdom pattern
-> Reads Patterns/extract_wisdom/system.md
-> Applies pattern to content
-> Returns structured IDEAS, INSIGHTS, QUOTES, etc.

Example 2: Update patterns

User: "Update fabric patterns"
-> Invokes UpdatePatterns workflow
-> Runs git pull from upstream fabric repository
-> Syncs patterns to local Patterns/ directory
-> Reports pattern count

Example 3: Create threat model

User: "Use fabric to create a threat model for this API"
-> Invokes ExecutePattern workflow
-> Selects create_threat_model pattern
-> Applies STRIDE methodology
-> Returns structured threat analysis

---

Quick Reference

Pattern Execution (Native - No CLI Required)

Instead of calling fabric -p pattern_name, LifeOS executes patterns natively:

1. Reads Patterns/{pattern_name}/system.md
2. Applies pattern instructions directly as prompt
3. Returns results without external CLI calls

When to Use Fabric CLI Directly

Only use fabric command for:

• -y URL - YouTube transcript extraction
• -u URL - URL content fetching (when native fetch fails)

Most Common Patterns

Intent	Pattern	Description
Extract insights	extract_wisdom	IDEAS, INSIGHTS, QUOTES, HABITS
Summarize	summarize	General summary
5-sentence summary	create_5_sentence_summary	Ultra-concise
Threat model	create_threat_model	Security threat analysis
Analyze claims	analyze_claims	Fact-check claims
Improve writing	improve_writing	Writing enhancement
Code review	review_code	Code analysis
Main idea	extract_main_idea	Core message extraction

Full Pattern Catalog

Browse the Patterns/ directory for the complete list of 240+ patterns organized by category.

---

Native Pattern Execution

How it works:

User Request → Pattern Selection → Read system.md → Apply → Return Results

Pattern Structure:

Patterns/
├── extract_wisdom/
│   └── system.md       # The prompt instructions
├── summarize/
│   └── system.md
├── create_threat_model/
│   └── system.md
└── ...240+ patterns

Each pattern's system.md contains the full prompt that defines:

• IDENTITY (who the AI should be)
• PURPOSE (what to accomplish)
• STEPS (how to process input)
• OUTPUT (structured format)

---

Pattern Categories

Category	Count	Examples
Extraction	30+	extract_wisdom, extract_insights, extract_main_idea
Summarization	20+	summarize, create_5_sentence_summary, youtube_summary
Analysis	35+	analyze_claims, analyze_code, analyze_threat_report
Creation	50+	create_threat_model, create_prd, create_mermaid_visualization
Improvement	10+	improve_writing, improve_prompt, review_code
Security	15	create_stride_threat_model, create_sigma_rules, analyze_malware
Rating	8	rate_content, judge_output, rate_ai_response

---

Integration

Feeds Into

• Research - Fabric patterns enhance research analysis
• Blogging - Content summarization and improvement
• Security - Threat modeling and analysis

Uses

• fabric CLI - For YouTube transcripts (-y) and URL fetching (-u)
• Native execution - Direct pattern application (preferred)

---

File Organization

Path	Purpose
Patterns/	Local pattern storage (240+)
Workflows/	Execution workflows

---

Changelog

2026-01-18

• Initial skill creation (extracted from LIFEOS/TOOLS/fabric)
• Native pattern execution (no CLI dependency for most patterns)
• Two workflows: ExecutePattern, UpdatePatterns
• 240+ patterns organized by category
• LifeOS Pack ready structure

Gotchas

• fabric -y URL for YouTube extraction — don't scrape YouTube pages. fabric handles transcript extraction natively.
• Pattern names are exact. extract_wisdom not extractwisdom. Check fabric --list if unsure.
• Long content may exceed pattern context limits. For very long inputs, chunk the content or use a summarize pattern first.

Execution Log

After completing any workflow, append a single JSONL entry:

echo '{"ts":"'$(date -u +%Y-%m-%dT%H:%M:%SZ)'","skill":"Fabric","workflow":"WORKFLOW_USED","input":"8_WORD_SUMMARY","status":"ok|error","duration_s":SECONDS}' >> ~/.claude/LIFEOS/MEMORY/SKILLS/execution.jsonl

Replace WORKFLOW_USED with the workflow executed, 8_WORD_SUMMARY with a brief input description, and SECONDS with approximate wall-clock time. Log status: "error" if the workflow failed.