Enhanced Filesystem Observer Specification and Content-Wide Registries
Summary
A new section, "DataStore/Registry Handling for Content-Wide Syntax (Draft Guidance)", was added to the specification [Create-a-Content-Registry-for-Markdown-Files.md]. This section outlines the rationale, principles, and implementation patterns for using persistent JSON registries to track unique content-wide syntax, such as citations, media links, embeds, and images.
Key Additions
- Registry Rationale: Explained why registries are needed for deduplication, analytics, and extensibility.
- General Principles: Documented single source of truth, schema-driven validation, atomicity, and idempotency.
- Example Interfaces: Provided TypeScript interface examples for citation and media/image registries.
- Service Pattern: Described singleton and atomic update patterns for registry services.
- Implementation Checklist: Listed concrete steps for integrating registry-backed services into the observer pipeline.
- Pseudocode: Added example update flow for registry maintenance.
- Open Questions: Raised future-facing questions about batching, concurrency, and audit trails.
Impact
- Establishes a clear, extensible foundation for all future registry-backed content observation (citations, media, etc.).
- Enables robust, cross-file analytics and prevents data corruption or duplication.
- Promotes best practices for atomic updates and error handling in content registries.
Next Steps
- Refine this draft as the first registry-backed observer (e.g., citations) is stabilized.
- Extend the guidance to cover new content types as needed.
- Review open questions and iterate on the implementation pattern for concurrency and auditability.
See [Create-a-Content-Registry-for-Markdown-Files.md] for full details and evolving guidance.
Summary
The specification for the Filesystem Observer for Consistent Metadata in Markdown files was significantly updated to provide:
- Clearer architectural diagrams and event flow
- Stronger requirements for non-destructive, template-driven, and transparent automation
- A robust, append-only reporting mechanism
- Actionable feedback loops for both developers and content authors
- Explicit guidance for atomic, idempotent updates and error handling
Key Changes
- System Pillars: Now explicitly prohibits YAML libraries for frontmatter parsing, mandates custom parsers, and expands the definition of template-driven consistency.
- Architecture Overview: Updated the mermaid diagram to reflect new detection and handling logic.
- Reporting: Changed report file handling to be append-only, with period-based aggregation and manual bloat management.
- Activity Log: Standardized Obsidian-style backlink syntax for file references in logs.
- Implementation Guidance: Emphasized atomic, idempotent file writes, centralized user options, and modular content processors.
- Error Handling: Requires all errors, warnings, and changes to be logged and never silently swallowed.
- Open Questions: Added new questions about AI code assistant compliance, test suite generation, and guarantees against unintentional changes.
Impact
- Ensures robust, auditable, and reversible automation for Markdown metadata management
- Provides a clear foundation for extensibility, future registry-backed features, and safe developer collaboration
- Strengthens trust and transparency in content automation workflows
Next Steps
- Review with development and content teams for further feedback
- Begin implementation of atomic reporting and template-driven processing
- Continue to iterate on registry and test suite guidance
See [Filesystem-Observer-for-Consistent-Metadata-in-Markdown-files.md] for full specification details and ongoing updates.