Research Analysis - 2026-04-18
Overview
The current research queue is intentionally narrow: one investigation aimed at reducing risk before a larger content operation in music-study.
Key Patterns
- The main unknowns are operational rather than product-facing.
- Retry safety and partial-failure behavior matter more than throughput at this stage.
- This research should likely split into concrete implementation tasks once the risk map is finished.
Task Analysis
Map audio import pipeline risks before batch upload
music-studyResearchTo do
Problem
The audio import pipeline has not been stress-checked for larger batches, so failure modes are still too opaque.
Likely causes
- Validation rules may be distributed across several steps.
- Partial failures may leave the local state harder to reconcile.
- Retry behavior may not distinguish safe retries from duplicate work.
Relevant files/modules
- import pipeline entrypoints
- audio validation logic
- batch upload bookkeeping
Suggested approach
- Trace the pipeline from file discovery to final persistence.
- List the points where duplicate names, malformed assets, or partial saves can occur.
- Convert the highest-confidence research findings into implementation tasks with explicit repository scope.
Recommended Execution Order
- Trace the current import flow end to end.
- Document the highest-risk breakpoints and retry semantics.
- Split concrete fixes into follow-up tasks only after the failure map is stable.
Quick Wins
- Record the exact validation checkpoints before running the first large batch.
- Capture whether retries are idempotent or create duplicate output.
Risks
- A batch run without a risk map may produce mixed good/bad local state.
- Research may stay vague unless it ends with concrete follow-up tasks.