Fabric#
An open-source framework (Go, MIT) for augmenting humans using AI. Created by daniel-miessler.
Mission: “human flourishing via AI augmentation”
Core Concept: Patterns#
Patterns are curated, well-structured prompts organized by real-world task. 251+ patterns covering:
- Content extraction (YouTube, podcasts, articles)
- Writing (essays, social media, documentation)
- Analysis (code, claims, debates, incidents, logs)
- Creation (art prompts, concept maps, changelogs)
- And many more
Each pattern is a directory with a system.md file. Markdown-based, clear instructions, System section focused.
Prompt Strategies#
Nine composable strategies applied as modifiers on top of any pattern:
| Strategy | Approach |
|---|---|
cot | Chain-of-Thought: step-by-step reasoning |
cod | Chain-of-Draft: minimal notes per step |
tot | Tree-of-Thought: multiple paths, select best |
aot | Atom-of-Thought: smallest independent sub-problems |
ltm | Least-to-Most: easiest to hardest |
self-consistent | Multiple paths with consensus |
self-refine | Answer → critique → refine |
reflexion | Answer → brief critique → refined answer |
standard | Direct answer |
This separates what to do (pattern) from how to reason (strategy).
Architecture#
- CLI-first, Unix philosophy:
echo "input" | fabric -p pattern_name - REST API server with Swagger docs
- 30+ AI providers (OpenAI, Anthropic, Gemini, Ollama, Bedrock, etc.)
- Per-pattern model mapping
- Shell aliases: each pattern becomes a command
- Obsidian integration for saving output as markdown
- Docker support, i18n (10 languages)
In the Ecosystem#
- Patterns are simpler predecessors to agent-skills-standard skills — same concept (curated prompt packages by task) but without scripts, progressive disclosure, or tool integration
- Strategies implement the prompt-engineering-patterns from academic literature
- Model-agnostic like scion is harness-agnostic
- Obsidian integration connects to the llm-wiki-pattern