author-strategylisted

# /author-strategy — PubMed Author Strategy Analysis ## Purpose Analyze a researcher's PubMed publication portfolio to reverse-engineer their research strategy. Produces a CSV dataset, 7 visualizations, and a strategy report. ## Prerequisites - Python 3.10+ with `biopython`, `pandas`, `matplotlib`, `seaborn` - Scripts: `${CLAUDE_SKILL_DIR}/fetch_pubmed.py`, `${CLAUDE_SKILL_DIR}/analyze_patterns.py` ## Workflow ### Step 1: Gather Input Ask the user for: 1. **Author name** (PubMed format, e.g., "Kim DK" or "Lee KS") 2. **Last name** for position classification (auto-detected if ambiguous) 3. **Output directory** (default: `~/.local/cache/author-strategy/{AuthorName}/`) ### Step 2: Fetch PubMed Data ```bash python "${CLAUDE_SKILL_DIR}/fetch_pubmed.py" "{Author Name}" \ --last-name "{LastName}" \ --output "{output_dir}/data/{name}_publications.csv" \ --email "{user_email}" ``` Review the console summary (total count, study type distribution, author position). If count is 0, suggest alternative name formats (e.g., "Yon DK" vs "Yon D" vs "Yon Dong Keon"). ### Step 3: Generate Visualizations and Report ```bash python "${CLAUDE_SKILL_DIR}/analyze_patterns.py" "{output_dir}/data/{name}_publications.csv" \ --output-dir "{output_dir}/report/" \ --author-name "{Author Name}" ``` This produces: - 7 PNG charts (01-07) - `analysis_report.md` with strategy breakdown ### Step 4: Interpret and Present Read `analysis_report.md` and present to the user: 1. **Executive s