Sorting LiteLLM GitHub issues by difficulty to implement. Higher = harder.

{
Issue 32951 is harder because it requires tracing and safely normalizing heterogeneous streaming data across Anthropic compatibility, completion assembly, logging, error handling, and regression tests. Issue 29536 is comparatively localized to fixture naming/path packaging with straightforward platform-specific validation.
}
https://github.com/berriai/litellm/issues/32951 5:1 https://github.com/berriai/litellm/issues/29536

Sorting LiteLLM GitHub issues by difficulty to implement. Higher = harder.

{
The left issue requires tracing response normalization across multiple compatibility layers and client versions, with higher uncertainty around streaming, schema, and provider-specific behavior. The right issue is comparatively contained in logging configuration and level propagation, likely involving a focused proxy/runtime change and regression tests.
}
https://github.com/berriai/litellm/issues/25848 5:1 https://github.com/berriai/litellm/issues/10788

Sorting LiteLLM GitHub issues by difficulty to implement. Higher = harder.

{
The right issue is harder because it requires designing and integrating a new configuration surface across proxy parsing, validation, runtime behavior, persistence or deployment workflows, backward compatibility, and comprehensive testing. The left issue is comparatively scoped to diagnosing and fixing a startup migration-timeout regression, though environment-specific database behavior adds some uncertainty.
}
https://github.com/berriai/litellm/issues/27287 3:1 https://github.com/berriai/litellm/issues/23976

Sorting LiteLLM GitHub issues by difficulty to implement. Higher = harder.

{
The right requires a code-path change involving cloud authorization behavior and regression validation, while the left is primarily a documentation clarification with limited implementation risk.
}
https://github.com/berriai/litellm/issues/33142 4:1 https://github.com/berriai/litellm/issues/27072

Sorting LiteLLM GitHub issues by difficulty to implement. Higher = harder.

{
Budget rollover is harder because it affects backend accounting invariants, persistence, reset scheduling, concurrent updates, configuration across entity types, and financial edge-case testing. Dashboard i18n has broader content scope but is comparatively isolated to frontend localization infrastructure and translation coverage.
}
https://github.com/berriai/litellm/issues/32603 5:3 https://github.com/berriai/litellm/issues/19730

Sorting LiteLLM GitHub issues by difficulty to implement. Higher = harder.

{
The right-hand task spans asynchronous streaming control flow, fallback orchestration, and cross-path behavioral testing, with greater risk of regressions. The left-hand task is a localized input-normalization change with a comparatively narrow provider-specific scope.
}
https://github.com/berriai/litellm/issues/28216 5:1 https://github.com/berriai/litellm/issues/28706

Sorting LiteLLM GitHub issues by difficulty to implement. Higher = harder.

{
The left task is harder because it requires a robust recursive transformation of arbitrary nested schemas, careful provider-specific behavior, and broad regression coverage. The right task is comparatively localized: add a guarded post-call persistence path while preserving existing limiter semantics.
}
https://github.com/berriai/litellm/issues/27821 3:2 https://github.com/berriai/litellm/issues/31880

Sorting LiteLLM GitHub issues by difficulty to implement. Higher = harder.

{
Issue 35136 is harder because it requires coordinated instrumentation across several asynchronous workflows, metric schema and label design, exporter integration, and broad validation. Issue 33323 is primarily a localized policy/control-flow correction with focused regression tests, though its failure semantics warrant careful security review.
}
https://github.com/berriai/litellm/issues/35136 4:1 https://github.com/berriai/litellm/issues/33323

Sorting LiteLLM GitHub issues by difficulty to implement. Higher = harder.

{
The left issue is harder because it affects shared routing state, cache-lifetime semantics, configuration behavior, and multi-deployment correctness, requiring broader regression coverage. The right issue is comparatively localized to parameter propagation and token-counting tests.
}
https://github.com/berriai/litellm/issues/28427 3:1 https://github.com/berriai/litellm/issues/27113

Sorting LiteLLM GitHub issues by difficulty to implement. Higher = harder.

{
The Prisma reconnection problem is harder because it involves database-client lifecycle management, subprocess failure recovery, proxy shutdown behavior, Kubernetes restart interactions, and reliable reproduction/testing. The command-line launch problem is comparatively narrow and likely limited to installation, PATH, or invocation diagnostics.
}
https://github.com/berriai/litellm/issues/26886 5:1 https://github.com/berriai/litellm/issues/35469