Fileregister: Tagging and reference layer for your files, in plain text
summary
Fileregister provides a way to track files using permanent IDs and plain-text indexes, ensuring that references to files remain valid even if the files are renamed or moved. By storing metadata in JSONL and Markdown files, it creates a portable, self-documenting system that outlasts OS-specific file organization. The system separates the actual file location from its identity, allowing users to maintain complex collections and binders across different machines.
key points
- The system uses a JSONL index as the source of truth, allowing files to be grouped into 'binders' regardless of their actual folder location.
- Permanent IDs are stored in file extended attributes (xattrs), enabling the tool to resolve a file's path even after it has been moved or renamed.
- Metadata is stored in Markdown sidecar files with YAML blocks, making the data human-readable, searchable via grep, and portable across different operating systems.
who should read it
Power users and archivists who need a robust way to organize large collections of files and maintain permanent links to documents across different drives or computers.
discussion positive
consensus
Users generally agree that the tool provides value by creating durable links to files that survive renaming or moving, which solves a common problem with traditional file paths. The sentiment is cautious but curious, with some users questioning the use cases compared to standard directory structures. The author's explanations clarify that the tool functions as a cross-machine tagging system and a database of files using JSONL files and markdown sidecars.
top insight
The most valuable perspective is that treating file organization as a database rather than a strict tree folder structure allows for more flexible grouping and collections. By using durable IDs and sidecar files, users can create virtual bundles of files regardless of their physical location on the disk. This approach transforms the file system from a a simple storage hierarchy into a searchable, relational metadata layer.
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