Sidecar Lint & Repair
Maintains structural integrity and metadata accuracy for citation sidecars within research corpora.
The Sidecar Lint & Repair skill provides essential hygiene for citation-heavy research projects by validating and repairing the internal structure of citation sidecar files. It automatically identifies missing frontmatter, repairs malformed headers, detects 'orphan' citations with no edges, and backfills missing author or affiliation data from analysis documents. By canonicalizing organization names to PROF-O slugs and ensuring referential consistency, it streamlines the management of large-scale cognitive architectures and AI-augmented software development research.
Key Features
01Structural validation of sidecar frontmatter and required sections
02Dry-run and real-time repair modes with detailed reporting
03Automatic author backfill from analysis citation blocks
04Canonicalization of affiliations to standardized PROF-O slugs
05Detection of zero-edge orphan sidecars across the corpus
06147 GitHub stars
Use Cases
01Validating the integrity of a citation graph before performing research analysis
02Cleaning up metadata in a large academic or technical research corpus
03Automating the backfilling of author information from reference documents