Fabric is a command-line framework that turns a curated library of prompt “patterns” into reusable, automatable workflows for large language models. Instead of repeatedly crafting ad-hoc prompts, you pick a pattern (for research, summarization, brainstorming, code review, and more) and feed it inputs or files. The tool standardizes execution with configuration files and environment variables, enabling reproducible runs across different models and providers. Patterns can be customized with variables, chained into pipelines, and applied to entire directories, which helps scale editorial or analytical tasks. A growing catalog of community patterns serves as a knowledge base for effective prompt engineering in practical contexts. In short, Fabric makes LLM work predictable and scriptable, so teams can share methods rather than one-off prompts.
Features
- Ingests and indexes OSINT and threat intelligence datasets for exploration
- Offers interactive UI for querying, filtering, and visualizing structured data
- Built upon modern data stacks for efficient indexing and search
- Extensible plugin architecture for integrating new data sources or analytics
- Designed for incident response and threat hunting workflows
- Open-source under a permissive license, enabling customization and local deployment