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Classifies and organizes literature by theme, method, and conclusion; use when you need to batch-read a folder of PDF/MD/DOCX/TXT files and output a structured CSV for literature reviews and annotation management.

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Source: https://github.com/aipoch/medical-research-skills

Bibliography

When to Use

  • You are conducting a literature review and need consistent summaries plus structured metadata (theme/method/conclusion) across many papers.
  • You have a mixed-format reading folder (.pdf, .md, .docx, .txt) and want a single CSV for downstream analysis (e.g., Excel, R, Python).
  • You need to organize annotations by keywords (theme), experimental methods (method), and key conclusions (conclusion).
  • You want a two-step pipeline: first generate a human-readable summary Markdown, then generate a machine-friendly CSV from that Markdown.
  • You need robust handling of PDFs by converting them to Markdown first (via pdf-extract) and then using only Markdown content for extraction.

Key Features

  • Batch scans an input directory for .pdf, .md, .docx, and .txt literature files.
  • Converts PDFs to Markdown via pdf-extract, then ignores non-Markdown artifacts (e.g., image folders).
  • Extracts and normalizes, per document:
    • Title
    • Summary (prefer original abstract)
    • Keywords (theme)
    • Experimental Methods (method names only)
    • Key Conclusions (single sentence)
    • Commentary (one-sentence, tactful evaluation)
  • Produces exactly two outputs:
    1. A consolidated Summary Markdown saved under outputs/
    2. A single CSV generated from that Summary Markdown
  • Enforces UTF-8 output to prevent garbled characters; fills missing fields with "Not recognized" instead of leaving blanks.
  • Uses the CSV field order and headers defined in assets/bibliography_template.csv.

Dependencies

  • pdf-extract (version: not specified; required when PDFs are present)
  • Input formats supported (no external version constraints specified):
    • PDF
    • Markdown (.md)
    • DOCX (.docx)
    • Plain text (.txt)

Example Usage

Goal

Read all literature files in a folder, generate a consolidated summary Markdown, then generate a CSV following assets/bibliography_template.csv.

Inputs

  • Input directory (example): ./inputs/literature/
  • Output directory: ./outputs/
  • Output CSV path (example): ./outputs/bibliography.csv

Expected Outputs (exactly two files)

  • ./outputs/bibliography_summary.md
  • ./outputs/bibliography.csv

Example Summary Markdown Structure (generated first)

# Bibliography Summary

## Document 1
- Title: <Title>
- Summary: <Prefer the original Abstract; if missing, use the closest equivalent section>
- Keywords: keyword1 | keyword2 | keyword3
- Experimental Methods: <method1; method2; ... (names only)>
- Key Conclusions: <one sentence covering all main points>
- Commentary: <one tactful sentence>

## Document 2
...

Example CSV (generated from the Summary Markdown)

The CSV must follow the header order defined in:

  • assets/bibliography_template.csv

Rules:

  • One row per document.
  • No empty cells; use Not recognized when extraction fails.
  • Save as UTF-8.

Implementation Details

1) Input Reading and Normalization

  • Traverse the input directory and process files with extensions:
    • .pdf, .md, .docx, .txt

PDF handling

  • If PDFs exist, convert them to Markdown using pdf-extract.
  • Use only the generated .md content; ignore image directories or other byproducts.
  • Locate pdf-extract as follows:
    1. First, look for a sibling skill directory containing SKILL.md at the same level as this skill’s parent directory.
    2. If not found, ask the user to confirm the actual pdf-extract path.

DOCX handling

  • Extract body text while preserving title/paragraph order as much as possible.

MD/TXT handling

  • Read text directly.
  • If garbled characters appear or key fields cannot be recognized, attempt to detect and read using the original encoding (commonly GB18030 / GBK) before extraction.

2) Generate the Summary Markdown First (Single Source of Truth)

Before producing the CSV, generate a consolidated Summary Markdown containing, for each document:

  • Title
  • Summary
    • Prefer the original Abstract.
    • If no “Abstract” exists, use the closest equivalent section (e.g., “Summary”, “Highlights”, or an “Objective–Method–Result–Conclusion” style segment).
  • Keywords
  • Experimental Methods
  • Key Conclusions
  • Commentary
    • Exactly one sentence.
    • Avoid harsh criticism; if the work has low value, use tactful phrasing.

This Summary Markdown must be saved with UTF-8 encoding and stored under outputs/. The CSV must be generated only from this Markdown (not directly from raw files).

3) Field Extraction Rules (Theme / Method / Conclusion)

  • Keywords (theme)
    • Prefer the original keywords from the document.
    • Separate multiple keywords with |.
    • If no keywords are found, generate 3–5 keyword phrases based on the abstract and append:
      • (generated based on abstract)
  • Experimental Methods (method)
    • Output method names only (no long descriptions).
  • Key Conclusions (conclusion)
    • One sentence that covers all main points.

4) CSV Output Constraints

  • Output exactly one CSV file at the end.
  • CSV field order and headers must match assets/bibliography_template.csv.
  • Encoding must be UTF-8 to avoid garbled characters.
  • If any field cannot be extracted, write Not recognized (never leave empty).
  • Only two files may be generated in total:
    1. Summary Markdown
    2. CSV
  • No temporary/intermediate/auxiliary files may be left behind (including extracted text dumps, caches, logs, images, backups). If conversion/extraction requires intermediate artifacts, keep them in memory or ensure all non-target files are deleted before final output.
  • Do not use PowerShell to directly write/manipulate CSV/Markdown to avoid encoding/newline issues; always generate and save using UTF-8.

Reference

  • Detailed rules and field descriptions: references/guide.md
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