Fabric GitHub Repository#

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Author: daniel-miessler

Summary#

fabric is an open-source framework (Go, MIT) for augmenting humans using AI. Its core contribution is Patterns — 251+ curated, well-structured prompts organized by real-world task. Also implements composable prompt strategies (CoT, ToT, Reflexion, etc.) as modifiers on top of patterns. Model-agnostic with 30+ provider integrations.

Key Takeaways#

  • Patterns as the fundamental unit: Fabric’s insight is that AI has a capabilities problem but an integration problem. Patterns solve this by packaging prompts as reusable, discoverable, shareable units organized by task. 251+ patterns covering everything from YouTube extraction to academic paper summarization.
  • Pattern design principles: Markdown for readability, extremely clear instructions, System section almost exclusively. Each pattern is a directory with a system.md file.
  • Composable strategies: Nine prompt strategies (CoT, CoD, ToT, AoT, LtM, self-consistent, self-refine, reflexion, standard) applied as modifiers on top of any pattern. Stored as JSON. This separates what to do (pattern) from how to reason (strategy).
  • CLI-first, Unix philosophy: Pipe input, compose with other tools. echo "input" | fabric --strategy cot -p analyze_code. Shell aliases turn each pattern into a command.
  • Model-agnostic: 30+ providers. Per-pattern model mapping via environment variables.
  • Obsidian integration: Save output as dated markdown files — directly relevant to the llm-wiki-pattern.
  • Community-driven: Open source pattern library. The “wisdom of crowds” approach to prompt curation.

Connections#

  • Patterns are conceptually similar to skills in the agent-skills-standard — both are curated prompt packages organized by task. But patterns are simpler (just a system.md) while skills support scripts, references, assets, and progressive disclosure.
  • Fabric’s strategies map directly to the prompt-engineering-patterns described in academic literature and the ten-pillars-agentic-skill-design framework (Pillar 5).
  • Fabric is model-agnostic like scion is harness-agnostic — both abstract over the underlying AI provider.

See Also#

Backward Evaluating Agent Skills Caparas Kiro Autonomous Agent Forward