Literature Experiment Extract

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

When to Use

• You have a paper converted to Markdown (e.g., via PDF-to-Markdown) and need to extract cell/animal models used in experiments.
• You need a structured list of experimental methods/protocols described in the paper, with traceable evidence.
• You want to compile biomarkers / detection indicators (e.g., genes, proteins, assays, readouts) reported in the study.
• You need standardized outputs for downstream analysis: one Markdown summary plus three CSV tables.
• The paper Markdown includes page markers (e.g., ## Page XX) and you want evidence organized by page.

Key Features

• Extracts three entity groups from paper Markdown:
  • Experimental models (cell lines, animal models, strains, genotypes, etc.)
  • Experimental methods (assays, protocols, instruments, conditions)
  • Biomarkers / indicators (targets, readouts, measured variables)
• Produces evidence-backed results (citations/excerpts preserved and traceable to the source).
• Supports page-aware evidence organization when the input includes pagination headers like ## Page XX.
• Outputs are fixed and standardized:
  • 1 Markdown summary
  • 3 CSV files: models / methods / biomarkers
• Uses a predefined template and extraction rules:
  • Requirements and consistency rules: references/guide.md
  • Output template: assets/template.md

Dependencies

• None (documentation-driven workflow).
• Input assumption: paper content is available as Markdown, typically generated by a PDF-to-Markdown tool.

Example Usage

Input

A paper converted to Markdown, ideally with page headers:

## Page 1
... text describing "C57BL/6 mice" and "Western blot" ...

## Page 2
... text describing "ELISA" and "IL-6 levels" ...

Steps

1. Open the paper Markdown (typically produced by PDF-to-Markdown tools).
2. Extract models, methods, and biomarkers page by page.
3. Follow:
   • Extraction rules and evidence requirements: references/guide.md
   • Output template: assets/template.md
4. Output exactly:
   • outputs/{Paper Abbreviation}-experiment-summary.md
   • outputs/{Paper Abbreviation}-models.csv
   • outputs/{Paper Abbreviation}-methods.csv
   • outputs/{Paper Abbreviation}-biomarkers.csv

Output (required)

• All final outputs must be UTF-8 encoded.
• Output must be produced directly (no confirmation steps or optional branches).
• Evidence excerpts must remain in the original language of the source literature.

Implementation Details

• Input parsing

  • Read the paper Markdown as the sole input source.
  • If pagination headers like ## Page XX exist, prioritize attaching evidence to the corresponding page.

• Extraction rules

  • Apply entity definitions, allowed/expected fields, normalization rules, and evidence formatting as specified in references/guide.md.

• Output formatting

  • Generate outputs using assets/template.md as the canonical structure.
  • Add rows as needed while preserving evidence citations/excerpts.
  • The output set is fixed: 1 Markdown summary + 3 CSVs (models/methods/biomarkers).

• Paths and naming

  • Default output directory: outputs/
  • Naming:
    • Markdown: outputs/{Paper Abbreviation}-experiment-summary.md
    • CSVs:
      • outputs/{Paper Abbreviation}-models.csv
      • outputs/{Paper Abbreviation}-methods.csv
      • outputs/{Paper Abbreviation}-biomarkers.csv

• Language

  • Output language should be Chinese by default (or the user-requested language if specified).
  • Evidence excerpts must remain in the original language of the source text.

When Not to Use

• Do not proceed when required input files, identifiers, parameters, or context are missing — ask the user to provide them first.
• Do not assume capabilities beyond this skill's declared scope when the user requests external operations or inferences.
• Do not proceed without user confirmation when overwriting existing results, executing high-cost batch operations, or expanding task scope.