github.com/danielmiessler/Fabric

Fabric is fundamentally a CLI application for AI-powered text processing that happens to expose some Go packages. In production, this creates friction: the library assumes CLI patterns, with heavy reliance on global state and filesystem operations that don't mesh well with server applications. The frequent releases (minor version bumps multiple times weekly) introduce breaking changes without semantic versioning discipline, making dependency management a headache.

Resource management is a concern - there's no built-in connection pooling for API calls, and timeout configurations are scattered across different command implementations rather than centralized. Error handling tends toward log-and-exit patterns appropriate for CLI but problematic for long-running services. Observability is minimal - you get stdout/stderr logging but no structured logging hooks or metrics integration points.

The actual pattern API is interesting for batch text processing jobs, but wrapping it in proper retry logic, circuit breakers, and monitoring requires significant work. If you need the specific AI patterns Fabric provides, budget time for building a robust integration layer around it.

Fabric is primarily a CLI tool for AI prompting workflows, not a traditional Go library. When you import it, you're not getting well-defined APIs for building applications - you're getting the internals of a command-line tool. The documentation focuses almost entirely on CLI usage, leaving library consumers guessing how to integrate components programmatically.

The package structure exposes internal implementation details without clear boundaries between public and private APIs. Error messages often reference CLI flags and file paths rather than providing context useful for programmatic usage. Common tasks like setting up a pattern executor or managing AI providers require diving into the CLI source code to understand the intended flow.

Debugging is frustrating because the codebase assumes CLI context. Stack Overflow has minimal coverage, and GitHub issues primarily address CLI features rather than library integration. If you need AI prompt management in Go, you'll spend more time reverse-engineering this tool than building your feature.

Fabric is an AI prompt orchestration tool that wraps LLM APIs with pre-built patterns. In practice, it feels more like a CLI wrapper around API calls than a production-ready Go library. The package handles sensitive API keys through environment variables and configuration files, but lacks proper secret management patterns like integration with credential stores or key rotation mechanisms.

The error handling is particularly concerning - API responses and failures often expose full request/response bodies in logs, potentially leaking sensitive data or prompt injection attempts. Input validation is minimal; user-supplied prompts and patterns are passed nearly verbatim to LLM APIs without sanitization or length limits. There's no built-in rate limiting, retry backoff logic, or circuit breaker patterns despite making external API calls.

The authentication model is simplistic (just API key passthrough), and there's no guidance on implementing proper authorization when wrapping this in a service. TLS configuration relies entirely on Go's defaults with no customization options. The project moves fast with frequent releases, but dependency management feels loose with several transitive dependencies that aren't actively audited for CVEs.