Anyfile2gbrain

Setup

Run this once before first use:

chmod +x ~/.claude/skills/AnyFile2Gbrain/setup.sh
~/.claude/skills/AnyFile2Gbrain/setup.sh

Workflow

When user provides a file path:

1. Detect format from extension
2. Convert to Markdown using appropriate tool
3. Auto-classify based on filename/content keywords
4. Write to brain directory (~/brain/<category>/)
5. Sync and embed: gbrain sync --repo ~/brain && gbrain embed --stale

Auto-Classification Rules

Analyze filename and content to determine target directory:

Slug generation: lowercase, hyphens, remove special chars

Conversion Commands

Excel (.xlsx, .xls) → Markdown

python3 -c "
import pandas as pd
import sys

file = '$FILE_PATH'
xlsx = pd.ExcelFile(file)
md = ''

for sheet in xlsx.sheet_names:
    df = pd.read_excel(xlsx, sheet_name=sheet)
    md += f'## Sheet: {sheet}\n\n'
    md += df.fillna('').to_markdown(index=False)
    md += '\n\n'

print(md)
" > /tmp/converted.md

PowerPoint (.pptx) → Markdown

python3 -c "
from pptx import Presentation
import sys

prs = Presentation('$FILE_PATH')
md = ''

for slide_num, slide in enumerate(prs.slides, 1):
    md += f'## Slide {slide_num}\n\n'
    for shape in slide.shapes:
        if hasattr(shape, 'text') and shape.text.strip():
            md += shape.text.strip() + '\n\n'
    for shape in slide.shapes:
        if shape.has_table:
            table = shape.table
            rows = []
            for row in table.rows:
                rows.append([cell.text.strip() for cell in row.cells])
            if rows:
                header = '| ' + ' | '.join(rows[0]) + ' |'
                separator = '| ' + ' | '.join(['---'] * len(rows[0])) + ' |'
                body = '\n'.join(['| ' + ' | '.join(r) + ' |' for r in rows[1:]])
                md += header + '\n' + separator + '\n' + body + '\n\n'

print(md)
" > /tmp/converted.md

Word (.docx) → Markdown

pandoc '$FILE_PATH' -t markdown --wrap=none > /tmp/converted.md

Or fallback with python-docx:

python3 -c "
from docx import Document

doc = Document('$FILE_PATH')
md = ''

for para in doc.paragraphs:
    style = para.style.name.lower()
    text = para.text.strip()
    if not text:
        continue
    if 'heading 1' in style:
        md += f'# {text}\n\n'
    elif 'heading 2' in style:
        md += f'## {text}\n\n'
    elif 'heading 3' in style:
        md += f'### {text}\n\n'
    else:
        md += text + '\n\n'

for table in doc.tables:
    rows = [[cell.text.strip() for cell in row.cells] for row in table.rows]
    if rows:
        header = '| ' + ' | '.join(rows[0]) + ' |'
        separator = '| ' + ' | '.join(['---'] * len(rows[0])) + ' |'
        body = '\n'.join(['| ' + ' | '.join(r) + ' |' for r in rows[1:]])
        md += '\n' + header + '\n' + separator + '\n' + body + '\n\n'

print(md)
" > /tmp/converted.md

PDF → Markdown

pandoc '$FILE_PATH' -t markdown --wrap=none > /tmp/converted.md 2>/dev/null || \
python3 -c "
import pdfplumber

with pdfplumber.open('$FILE_PATH') as pdf:
    md = ''
    for page in pdf.pages:
        text = page.extract_text()
        if text:
            md += text + '\n\n'
    print(md)
" > /tmp/converted.md

CSV → Markdown

python3 -c "
import pandas as pd

df = pd.read_csv('$FILE_PATH')
print(df.fillna('').to_markdown(index=False))
" > /tmp/converted.md

Import to Gbrain

SLUG=$(basename '$FILE_PATH' | sed 's/\.[^.]*$//' | tr '[:upper:]' '[:lower:]' | sed 's/[^a-z0-9]/-/g' | sed 's/^-//;s/-$//')
CATEGORY="<determined-category>"

cat > ~/brain/$CATEGORY/$SLUG.md << 'EOF'
---