Skip to content

analyze-bucket-type.md

Latest commit

 

History

History
74 lines (54 loc) · 3.05 KB

analyze-bucket-type.md

File metadata and controls

74 lines (54 loc) · 3.05 KB
argument-hint <bucket-type>
description Analyze a bucket type implementation to identify all behaviors and configurations

Given the bucket type ID "$ARGUMENTS" (e.g., "json", "mdx", "typescript"), analyze the implementation code to identify ALL bucket-specific behaviors, configurations, and characteristics.

Instructions

  1. Locate where this bucket type is processed in the codebase by searching for the bucket type string. Start with the main loader composition/pipeline code.

  2. Trace the complete execution pipeline for this bucket:

    • List every function/loader in the processing chain, in order
    • For each function/loader, read its implementation to understand:
      • Input parameters it receives
      • Transformations it performs on the data
      • Output format it produces
      • Any side effects or file operations

  3. Identify configuration parameters by:

    • Finding which variables are passed into the loaders (e.g., lockedKeys, ignoredKeys)
    • Tracing these variables back to their source (configuration parsing)
    • Determining if they're bucket-specific or universal

  4. Analyze file I/O behavior:

    • How are file paths constructed?
    • Does the path pattern contain locale placeholders that would create separate files?
    • What file operations are performed (read, write, create, delete)?
    • Are files overwritten or are new files created?
    • IMPORTANT: Note that "overwrites existing files completely" and "[locale] placeholder support" are mutually exclusive in practice:
      • If a bucket type stores all locales in a single file (like CSV with columns per locale), it overwrites that single file and does NOT support [locale] placeholders
      • If a bucket type creates separate files per locale using [locale] placeholders, each locale file is overwritten individually
      • Clarify which pattern the bucket type follows

  5. Examine data transformation logic:

    • How is the file content parsed?
    • What internal data structures are used?
    • How is the data serialized back to file format?
    • Are there any format-preserving mechanisms?

  6. Identify special behaviors by examining:

    • Conditional logic specific to this bucket
    • Error handling unique to this format
    • Any validation or normalization steps
    • Interactions between multiple loaders in the pipeline

  7. Determine constraints and capabilities:

    • What data types/structures are supported?
    • Are there any size or complexity limitations?
    • What happens with edge cases (empty files, malformed content)?

Required Depth

  • Read the ACTUAL implementation of each loader/function
  • Follow all function calls to understand the complete flow
  • Don't make assumptions - verify behavior in the code
  • Consider the order of operations in the pipeline

Output Format

List all findings categorized as:

  • Configuration parameters (with their types and defaults)
  • Processing pipeline (ordered list of transformations)
  • File handling behavior
  • Data transformation characteristics
  • Special capabilities or limitations
  • Edge case handling