Extract TOC data and trace article page ranges from magazine PDFs into .dat files.
npx skills add https://github.com/timfogarty1549/musmemSkills --skill musmem-toc
Please help me install this Agent Skill. Skill: musmem-toc Source: https://github.com/timfogarty1549/musmemSkills/tree/main/musmem-toc Command: npx skills add https://github.com/timfogarty1549/musmemSkills --skill musmem-toc
This Skill automates extracting table-of-contents data from scanned bodybuilding magazine PDFs and writing per-issue .dat entries, enabling efficient TOC management and article range tracing.
Run Phase 1 to extract TOC from a magazine PDF, then run Phase 2 to trace article page ranges and update per-issue .dat files.
High-intent search queries and answers about installing and using this skill.
You can trace article page ranges by running Phase 2 after TOC extraction, which uses pdfplumber to map each article to its precise PDF page range and updates the per-issue .dat files for online serving.
Yes, extracting PDF TOC data and tracing page ranges with this Skill requires a Python environment with the pdfplumber library installed to parse PDF structures and a local musmem workspace to store results.
The best way to convert scanned magazines into searchable data is a two-phase pipeline: extract TOC entries into .dat files, then trace precise PDF page ranges for each article to create per-article PDFs ready for indexing.
Generating per-article PDFs starts with extracting the TOC and tracing page ranges to populate .dat files, which provides the precise boundaries needed to split the full magazine PDF into individual searchable articles.
Incorrect page range tracing during PDF extraction often occurs when the source magazine scans have inconsistent formatting or missing TOC entries, so ensure Phase 1 accurately captures the table of contents before running Phase 2.
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