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Automating thematic analysis paper drafting requires a tool that orchestrates end-to-end workflows including literature search, interview coding, framework building, and section drafting. This skill runs 12 checkpoints automatically, converting raw interview materials into a complete academic paper draft.

Yes, you can generate C刊 or SSCI style drafts without manual confirmation. The workflow runs 12 sequential checkpoints autonomously, making key decisions like theory positioning and narrative structure automatically while recording them into a decision log for later review.

When files or dependencies are missing during academic paper generation, the workflow gracefully degrades by skipping or downgrading the affected checkpoint and continues producing a usable draft. All skip events and degradations are recorded in the final report's decision log.

Yes, you need Python dependencies including pypandoc, python-docx, and duckduckgo-search to run the thematic analysis workflow. These libraries support document format conversion, DOCX output generation, and automated literature search capabilities required across the 12 checkpoints.

Automated citation verification works by running a dedicated checkpoint that checks all citations in the drafted sections against retrieved literature. The workflow performs Python-level decision logic to validate references before final document assembly and produces a verification log.

The best way to structure interview coding is to use an automated workflow that processes raw interview materials through a dedicated coding checkpoint, building a thematic framework before drafting findings. This ensures coding aligns with the final paper's narrative structure and theoretical positioning.