github.com/slimtoolkit/slim

SlimToolkit is primarily a CLI tool for minifying and securing container images, and using it as a Go package requires understanding its internal architecture. The learning curve is steep because the package is structured around the tool's command implementations rather than as a library-first design. Documentation focuses heavily on CLI usage, leaving Go developers to dig through source code to understand how to integrate it programmatically.

When you do get it working, the core functionality is solid—image analysis and optimization work well. However, error messages can be cryptic when configuration is incorrect, often requiring you to trace through multiple layers of the codebase. The GitHub issues show maintainers are responsive, but most discussions center on CLI usage rather than programmatic integration.

Debugging is challenging because the package deals with low-level container operations. You'll need familiarity with Docker internals and be prepared to read through the CLI command implementations to understand proper API usage patterns. Common use cases like basic image slimming are easier through the CLI than the Go API.

SlimToolkit is primarily designed as a CLI tool for minifying container images, and its Go package reflects this heritage. When you import it programmatically, you're essentially wrapping CLI-style interfaces rather than working with idiomatic Go APIs. The package structure exposes internal command implementations that feel more like importing a binary's internals than a purpose-built library.

The type definitions are present but sparse on documentation. You'll find yourself reading command package source code to understand parameter structures and expected behaviors. Error handling follows CLI patterns with exit codes and stdout/stderr captures rather than structured errors, making programmatic error inspection awkward. IDE autocompletion works but doesn't provide much guidance without diving into implementation details.

For production use cases where you need the optimization capabilities embedded in your tooling, it's workable but requires patience. The actual container analysis and minification logic is solid, but the developer experience feels like an afterthought. Expect to spend time reading source code and experimenting to understand the right way to configure and invoke the optimization pipeline.

SlimToolkit is primarily a CLI-focused tool for analyzing and minifying container images, and using it as a Go library in production systems requires careful consideration. The package exposes internal APIs that power the CLI, but documentation for programmatic usage is sparse. You'll spend time reading source code to understand how to properly initialize the engine, configure sensors, and handle the analysis lifecycle.

Resource management requires attention - the tool spawns Docker containers for analysis and can consume significant memory during image inspection. There's no built-in connection pooling for Docker API calls, so you'll need to implement your own resource limits and timeouts. Error handling is functional but not always granular enough to distinguish between transient failures (network issues) versus permanent problems (malformed images).

The library works well for batch processing scenarios where you control the execution environment, but integrating it into high-throughput services requires custom wrappers for observability, retry logic, and graceful degradation. Configuration is flexible through structs, but defaults aren't always production-ready - you'll need to tune timeouts and resource limits based on your workload.