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Fabric

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danielmiessler
Fabric

Execute any of 240+ specialized prompt patterns natively across Extraction, Summarization, Analysis, Creation, Improvement, Security, Rating. Common: extract_wisdom, create_threat_model, analyze_claims, improve_writing, review_code, mermaid, youtube_summary. CLI used only for YouTube transcript (-y) and URL fallback (-u). Two workflows: ExecutePattern, UpdatePatterns. USE WHEN fabric, fabric pattern, run fabric, update patterns, threat model, analyze claims, improve writing, review code, mermaid, STRIDE, sigma rules. NOT FOR multi-agent investigation (Research) or content-adaptive extraction (ExtractWisdom).

Overview

Publisherdanielmiessler
RepositoryLifeOS
Skill nameFabric
Stars
19K
Forks
2.5K
Bundled files
299
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 299 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by danielmiessler on GitHub. Read the source before you install it.

Installation

Install the Fabric AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/danielmiessler/LifeOS.git /tmp/LifeOS
mkdir -p .claude/skills
cp -r /tmp/LifeOS/LifeOS/install/skills/Fabric .claude/skills/Fabric
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Fabric in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Fabric on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Fabric is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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:

    bash
    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/


Workflow Routing

WorkflowTriggerFile
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

IntentPatternDescription
Extract insightsextract_wisdomIDEAS, INSIGHTS, QUOTES, HABITS
SummarizesummarizeGeneral summary
5-sentence summarycreate_5_sentence_summaryUltra-concise
Threat modelcreate_threat_modelSecurity threat analysis
Analyze claimsanalyze_claimsFact-check claims
Improve writingimprove_writingWriting enhancement
Code reviewreview_codeCode analysis
Main ideaextract_main_ideaCore 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

CategoryCountExamples
Extraction30+extract_wisdom, extract_insights, extract_main_idea
Summarization20+summarize, create_5_sentence_summary, youtube_summary
Analysis35+analyze_claims, analyze_code, analyze_threat_report
Creation50+create_threat_model, create_prd, create_mermaid_visualization
Improvement10+improve_writing, improve_prompt, review_code
Security15create_stride_threat_model, create_sigma_rules, analyze_malware
Rating8rate_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

PathPurpose
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:

bash
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.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

and 140 more files.

Frequently asked questions

What does the Fabric AI skill do?

Execute any of 240+ specialized prompt patterns natively across Extraction, Summarization, Analysis, Creation, Improvement, Security, Rating. Common: extract_wisdom, create_threat_model, analyze_claims, improve_writing, review_code, mermaid, youtube_summary. CLI used only for YouTube transcript (-y) and URL fallback (-u). Two workflows: ExecutePattern, UpdatePatterns. USE WHEN fabric, fabric pattern, run fabric, update patterns, threat model, analyze claims, improve writing, review code, mermaid, STRIDE, sigma rules. NOT FOR multi-agent investigation (Research) or content-adaptive extractio...

Why use Fabric on TypingMind?

Because you install it once and use it with any model. Fabric is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Fabric in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/danielmiessler/LifeOS/tree/main/LifeOS/install/skills/Fabric. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Fabric?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Fabric?

As many as you like. As long as a model supports skills, you can use Fabric with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Fabric AI skill free?

Yes. It is published on GitHub by danielmiessler under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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