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