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Add eyeball plugin: document analysis with inline source screenshots

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Eyeball generates Word documents where every factual claim includes a
highlighted screenshot from the source material. Supports PDFs, Word
docs, and web URLs. Designed for verifying AI-generated document
analysis against the original source.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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2026-04-03 23:47:23 -07:00
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skills/eyeball/SKILL.md Normal file
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---
name: eyeball
description: 'Document analysis with inline source screenshots. When you ask Copilot to analyze a document, Eyeball generates a Word doc where every factual claim includes a highlighted screenshot from the source material so you can verify it with your own eyes.'
---
# Eyeball
Analyze documents with visual proof. When activated, Eyeball produces a Word document on the user's Desktop where every factual assertion includes an inline screenshot from the source material with the cited text highlighted in yellow.
## Activation
When the user invokes this skill (e.g., "use eyeball", "run eyeball on this", "eyeball this document"), respond with:
> **Eyeball is active.** I'll analyze the document and produce a Word doc with inline source screenshots so you can verify every claim with your own eyes.
Then follow the workflow below.
## Supported Sources
- **Local files:** Word documents (.docx, .doc), PDFs (.pdf), RTF files
- **Web URLs:** Any publicly accessible web page
## Tool Location
The Eyeball Python utility is located at:
```
<plugin_dir>/skills/eyeball/tools/eyeball.py
```
To find the actual path, run:
```bash
find ~/.copilot/installed-plugins -name "eyeball.py" -path "*/eyeball/*" 2>/dev/null
```
If not found there, check the project directory or the user's home directory for the eyeball repo.
## First-Run Setup
Before first use, check that dependencies are installed:
```bash
python3 <path-to>/eyeball.py setup-check
```
If anything is missing, run the setup script from the eyeball plugin directory:
```bash
bash <path-to>/setup.sh
```
Or install manually:
```bash
pip3 install pymupdf pillow python-docx playwright
python3 -m playwright install chromium
```
## Workflow
Follow these steps exactly. The order matters.
### Step 1: Read the source text
Before writing any analysis, extract and read the full text of the source document:
```bash
python3 eyeball.py extract-text --source "<path-or-url>"
```
Read the output carefully. Identify actual section numbers, headings, page numbers, and key language.
**CRITICAL:** Do not skip this step. Do not write analysis based on assumptions about how the document is structured. Read the actual text.
### Step 2: Write analysis with exact citations
For each point in your analysis, you must:
1. **Reference the correct section number as it appears in the document** (e.g., "Section 9" not "Section 8" because you assumed the numbering).
2. **Reference the correct page number** where the section appears in the extracted text.
3. **Select anchors that are verbatim phrases from the source** that directly support your claim.
### Step 3: Select anchors correctly
This is the most important step. Anchors determine what gets highlighted in the screenshots.
**DO:**
- Use verbatim phrases from the source text that directly support your assertion
- Use multiple anchors to span the full range of text the reader should see
- Use specific, uncommon phrases that appear only where you intend
**DO NOT:**
- Use generic topic labels (e.g., "Confidentiality") that appear throughout the document
- Use section titles alone when they appear as cross-references elsewhere
- Use single common words that match in many places
**Examples:**
WRONG -- uses a generic topic label that matches everywhere:
```json
{"anchors": ["User-Generated Content"], "target_page": 8}
```
RIGHT -- uses the specific language that supports the claim:
```json
{"anchors": ["retain ownership", "Ownership of Content, Right to Post"], "target_page": 8}
```
WRONG -- section title appears as a cross-reference on earlier pages:
```json
{"anchors": ["LIMITATION OF LIABILITY"]}
```
RIGHT -- includes the section number for precision, targets the correct page:
```json
{"anchors": ["12. LIMITATION OF LIABILITY", "INDIRECT", "CONSEQUENTIAL"], "target_page": 13}
```
### Step 4: Build the analysis document
Construct a JSON array of sections and call the build command:
```bash
python3 eyeball.py build \
--source "<path-or-url>" \
--output ~/Desktop/<title>.docx \
--title "Analysis Title" \
--subtitle "Source description" \
--sections '[
{
"heading": "1. Section Title",
"analysis": "Your analysis text here. Reference Section X on page Y...",
"anchors": ["verbatim phrase 1", "verbatim phrase 2"],
"target_page": 5,
"context_padding": 40
},
{
"heading": "2. Another Section",
"analysis": "More analysis...",
"anchors": ["exact quote from source"],
"target_pages": [10, 11],
"context_padding": 50
}
]'
```
Section object fields:
- `heading` (required): Section heading in the output document
- `analysis` (required): Your analysis text
- `anchors` (required): List of verbatim phrases from the source to search for and highlight
- `target_page` (optional): Single page number (1-indexed) to search on
- `target_pages` (optional): List of page numbers to search across (screenshots stitched vertically)
- `context_padding` (optional): Padding in PDF points above/below the anchor region (default: 40). Increase for more context.
### Step 5: Deliver the output
Save the output to the user's Desktop. Tell the user the filename and that they can open it to verify each claim against the highlighted source screenshots.
## Self-Check Before Delivery
Before saving the final document, mentally verify:
1. Does each section's analysis text reference the correct section number from the source?
2. Are the anchors verbatim phrases that appear on the target page?
3. Does each anchor directly support the claim in the analysis, not just relate to the same topic?
4. If the screenshot doesn't match the analysis, is the analysis wrong or is the anchor wrong? Fix whichever is incorrect.
## Notes
- The output document includes highlighted screenshots that are dynamically sized. If you provide multiple anchors, the screenshot expands to cover all of them.
- When a search term is not found, the output document will note this. If this happens, the anchor was likely not verbatim enough. Adjust and rebuild.
- For web pages, Playwright renders the page to PDF first. The resulting page numbers may differ from what you see in a browser. Use the extracted text output (step 1) to determine correct page numbers.
- If the user has already provided the source text or you have already read it in the current conversation, you can skip step 1. But always verify section numbers and page references against the actual text before writing analysis.

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skills/eyeball/tools/eyeball.py Executable file
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#!/usr/bin/env python3
"""
Eyeball - Document analysis with inline source screenshots.
Converts source documents (Word, PDF, web URL) to PDF, renders pages as images,
searches for cited text, highlights matching regions, and assembles an output
Word document with analysis text interleaved with source screenshots.
Usage (called by the Copilot CLI skill, not typically invoked directly):
python3 eyeball.py build \
--source <path-or-url> \
--output <output.docx> \
--sections sections.json
python3 eyeball.py setup-check
python3 eyeball.py convert --source <file.docx> --output <file.pdf>
python3 eyeball.py screenshot \
--source <file.pdf> \
--anchors '["term1", "term2"]' \
--page 5 \
--output screenshot.png
"""
import argparse
import io
import json
import os
import platform
import shutil
import subprocess
import sys
import tempfile
try:
import fitz # PyMuPDF
from PIL import Image, ImageDraw
from docx import Document
from docx.shared import Inches, Pt, RGBColor
except ImportError as e:
print(f"Missing dependency: {e}", file=sys.stderr)
print("Run setup.sh or: pip3 install pymupdf pillow python-docx playwright", file=sys.stderr)
sys.exit(1)
# ---------------------------------------------------------------------------
# Document conversion: source -> PDF
# ---------------------------------------------------------------------------
def convert_to_pdf(source_path, output_pdf_path):
"""Convert a document to PDF. Supports .docx, .doc, .rtf, .html, .htm."""
ext = os.path.splitext(source_path)[1].lower()
if ext == ".pdf":
if os.path.abspath(source_path) != os.path.abspath(output_pdf_path):
shutil.copy2(source_path, output_pdf_path)
return True
system = platform.system()
# Try Microsoft Word on macOS via AppleScript
if system == "Darwin" and ext in (".docx", ".doc", ".rtf"):
if os.path.exists("/Applications/Microsoft Word.app"):
if _convert_with_word_mac(source_path, output_pdf_path):
return True
# Try LibreOffice on any platform
soffice = shutil.which("libreoffice") or shutil.which("soffice")
if soffice and ext in (".docx", ".doc", ".rtf", ".odt", ".html", ".htm"):
if _convert_with_libreoffice(soffice, source_path, output_pdf_path):
return True
# Try Microsoft Word on Windows via COM
if system == "Windows" and ext in (".docx", ".doc", ".rtf"):
if _convert_with_word_windows(source_path, output_pdf_path):
return True
raise RuntimeError(
f"Cannot convert {ext} to PDF. Install Microsoft Word (macOS/Windows) "
f"or LibreOffice (any platform)."
)
def _convert_with_word_mac(source_path, output_pdf_path):
"""Convert using Microsoft Word on macOS via AppleScript."""
source_abs = os.path.abspath(source_path)
output_abs = os.path.abspath(output_pdf_path)
script = f'''
tell application "Microsoft Word"
open POSIX file "{source_abs}"
delay 2
set theDoc to active document
save as theDoc file name POSIX file "{output_abs}" file format format PDF
close theDoc saving no
end tell
'''
try:
result = subprocess.run(
["osascript", "-e", script],
capture_output=True, text=True, timeout=60
)
return result.returncode == 0 and os.path.exists(output_pdf_path)
except (subprocess.TimeoutExpired, FileNotFoundError):
return False
def _convert_with_libreoffice(soffice_path, source_path, output_pdf_path):
"""Convert using LibreOffice headless mode."""
with tempfile.TemporaryDirectory() as tmpdir:
try:
result = subprocess.run(
[soffice_path, "--headless", "--convert-to", "pdf",
"--outdir", tmpdir, source_path],
capture_output=True, text=True, timeout=120
)
if result.returncode != 0:
return False
basename = os.path.splitext(os.path.basename(source_path))[0] + ".pdf"
tmp_pdf = os.path.join(tmpdir, basename)
if os.path.exists(tmp_pdf):
shutil.move(tmp_pdf, output_pdf_path)
return True
except (subprocess.TimeoutExpired, FileNotFoundError):
pass
return False
def _convert_with_word_windows(source_path, output_pdf_path):
"""Convert using Microsoft Word on Windows via win32com."""
try:
import win32com.client
word = win32com.client.Dispatch("Word.Application")
word.Visible = False
doc = word.Documents.Open(os.path.abspath(source_path))
doc.SaveAs(os.path.abspath(output_pdf_path), FileFormat=17) # 17 = PDF
doc.Close()
word.Quit()
return True
except Exception:
return False
def render_url_to_pdf(url, output_pdf_path):
"""Render a web page to PDF using Playwright."""
try:
from playwright.sync_api import sync_playwright
except ImportError:
raise RuntimeError(
"Playwright is required for web URL support. "
"Run: pip3 install playwright && python3 -m playwright install chromium"
)
with sync_playwright() as p:
browser = p.chromium.launch(headless=True)
page = browser.new_page()
page.goto(url, wait_until="networkidle", timeout=30000)
# Clean up navigation/footer elements for cleaner output
page.evaluate("""
document.querySelectorAll(
'header, footer, nav, [data-testid="header"], [data-testid="footer"], '
+ '.site-header, .site-footer, #cookie-banner, .cookie-consent'
).forEach(el => el.remove());
""")
page.pdf(
path=output_pdf_path,
format="Letter",
print_background=True,
margin={"top": "0.5in", "bottom": "0.5in",
"left": "0.75in", "right": "0.75in"}
)
browser.close()
# ---------------------------------------------------------------------------
# Screenshot generation
# ---------------------------------------------------------------------------
def screenshot_region(pdf_doc, anchors, target_page=None, target_pages=None,
context_padding=40, dpi=200):
"""
Find anchor text in a PDF and capture the surrounding region as a highlighted image.
Args:
pdf_doc: An open fitz.Document.
anchors: List of search strings. The crop region expands to cover all of them.
target_page: Single 1-indexed page to search on.
target_pages: List of 1-indexed pages to search across (results stitched vertically).
context_padding: Extra padding in PDF points above/below the anchor region.
dpi: Render resolution.
Returns:
(image_bytes, page_label, (width, height)) or (None, None, None).
"""
if isinstance(anchors, str):
anchors = [anchors]
# Determine pages to search
if target_pages:
pages = [p - 1 for p in target_pages]
elif target_page:
pages = [target_page - 1]
else:
pages = list(range(pdf_doc.page_count))
# Collect hits across pages
page_hits = {}
for pg_idx in pages:
if pg_idx < 0 or pg_idx >= pdf_doc.page_count:
continue
page = pdf_doc[pg_idx]
hits_on_page = []
for anchor in anchors:
found = page.search_for(anchor)
if found:
hits_on_page.extend([(anchor, h) for h in found])
if hits_on_page:
page_hits[pg_idx] = hits_on_page
if not page_hits:
return None, None, None
zoom = dpi / 72
# If single page, render one region
if len(page_hits) == 1:
pg_idx = list(page_hits.keys())[0]
img = _render_page_region(pdf_doc, pg_idx, page_hits[pg_idx],
context_padding, zoom)
img_bytes = _img_to_bytes(img)
return img_bytes, f"page {pg_idx + 1}", img.size
# Multi-page: stitch vertically
images = []
pages_used = sorted(page_hits.keys())
for pg_idx in pages_used:
img = _render_page_region(pdf_doc, pg_idx, page_hits[pg_idx],
context_padding, zoom)
images.append(img)
stitched = _stitch_vertical(images)
img_bytes = _img_to_bytes(stitched)
if len(pages_used) > 1:
page_label = f"pages {pages_used[0]+1}-{pages_used[-1]+1}"
else:
page_label = f"page {pages_used[0]+1}"
return img_bytes, page_label, stitched.size
def _render_page_region(pdf_doc, pg_idx, hits_with_anchors, context_padding, zoom):
"""Render a cropped region of a PDF page with highlighted anchor text."""
page = pdf_doc[pg_idx]
page_rect = page.rect
all_rects = [h for _, h in hits_with_anchors]
min_y = min(r.y0 for r in all_rects)
max_y = max(r.y1 for r in all_rects)
crop_rect = fitz.Rect(
page_rect.x0 + 20,
max(page_rect.y0, min_y - context_padding),
page_rect.x1 - 20,
min(page_rect.y1, max_y + context_padding)
)
mat = fitz.Matrix(zoom, zoom)
pix = page.get_pixmap(matrix=mat, clip=crop_rect)
img = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)
# Highlight each anchor hit
draw = ImageDraw.Draw(img, "RGBA")
for anchor, rect in hits_with_anchors:
if rect.y0 >= crop_rect.y0 - 5 and rect.y1 <= crop_rect.y1 + 5:
x0 = (rect.x0 - crop_rect.x0) * zoom
y0 = (rect.y0 - crop_rect.y0) * zoom
x1 = (rect.x1 - crop_rect.x0) * zoom
y1 = (rect.y1 - crop_rect.y0) * zoom
draw.rectangle([x0-2, y0-2, x1+2, y1+2], fill=(255, 255, 0, 100))
# Border
ImageDraw.Draw(img).rectangle(
[0, 0, img.width - 1, img.height - 1],
outline=(160, 160, 160), width=2
)
return img
def _stitch_vertical(images, gap=4):
"""Stitch multiple images vertically with a small gap between them."""
total_height = sum(img.height for img in images) + gap * (len(images) - 1)
max_width = max(img.width for img in images)
stitched = Image.new("RGB", (max_width, total_height), (255, 255, 255))
y = 0
for img in images:
stitched.paste(img, (0, y))
y += img.height + gap
ImageDraw.Draw(stitched).rectangle(
[0, 0, stitched.width - 1, stitched.height - 1],
outline=(160, 160, 160), width=2
)
return stitched
def _img_to_bytes(img):
"""Convert PIL Image to PNG bytes."""
buf = io.BytesIO()
img.save(buf, format="PNG", quality=95)
buf.seek(0)
return buf
# ---------------------------------------------------------------------------
# Output document assembly
# ---------------------------------------------------------------------------
def build_analysis_doc(pdf_doc, sections, output_path, title=None, subtitle=None,
source_label=None, dpi=200):
"""
Build a Word document with analysis sections and inline source screenshots.
Args:
pdf_doc: An open fitz.Document (the source, already converted to PDF).
sections: List of dicts, each with:
- heading (str): Section heading
- analysis (str): Analysis text
- anchors (list[str]): Verbatim phrases from source to search and highlight
- target_page (int, optional): 1-indexed page to search on
- target_pages (list[int], optional): Multiple pages to search across
- context_padding (int, optional): Extra padding in PDF points (default 40)
output_path: Where to save the output .docx file.
title: Document title.
subtitle: Document subtitle.
source_label: Label for the source (e.g., filename or URL).
dpi: Screenshot resolution.
"""
doc = Document()
# Style
style = doc.styles["Normal"]
style.font.name = "Calibri"
style.font.size = Pt(11)
# Title
if title:
doc.add_heading(title, level=1)
if subtitle:
p = doc.add_paragraph()
run = p.add_run(subtitle)
run.font.size = Pt(11)
run.font.color.rgb = RGBColor(100, 100, 100)
doc.add_paragraph("")
# Sections
for i, section in enumerate(sections):
heading = section.get("heading", f"Section {i+1}")
analysis = section.get("analysis", "")
anchors = section.get("anchors", [])
target_page = section.get("target_page")
target_pages = section.get("target_pages")
padding = section.get("context_padding", 40)
doc.add_heading(heading, level=2)
doc.add_paragraph(analysis)
if anchors:
img_bytes, page_label, size = screenshot_region(
pdf_doc, anchors,
target_page=target_page,
target_pages=target_pages,
context_padding=padding,
dpi=dpi
)
if img_bytes:
# Source label
p = doc.add_paragraph()
anchor_text = ", ".join(f'"{a}"' for a in anchors[:3])
if len(anchors) > 3:
anchor_text += f" (+{len(anchors)-3} more)"
label = f"[Source: {source_label or 'document'}, {page_label}"
label += f" -- highlighted: {anchor_text}]"
run = p.add_run(label)
run.font.size = Pt(8)
run.font.color.rgb = RGBColor(120, 120, 120)
run.font.italic = True
p.paragraph_format.space_before = Pt(6)
p.paragraph_format.space_after = Pt(2)
# Screenshot
doc.add_picture(img_bytes, width=Inches(5.8))
doc.paragraphs[-1].paragraph_format.space_after = Pt(12)
else:
# Anchors not found
p = doc.add_paragraph()
run = p.add_run(
f"[Screenshot not available: could not find "
f"{', '.join(repr(a) for a in anchors)} in the source document]"
)
run.font.size = Pt(9)
run.font.italic = True
run.font.color.rgb = RGBColor(180, 50, 50)
# Footer note
doc.add_paragraph("")
note = doc.add_paragraph()
run = note.add_run(
"Generated by Eyeball. Each screenshot is captured from the source document "
"with cited text highlighted in yellow. Screenshots are dynamically sized to "
"cover the full range of text referenced in the analysis. Review the highlighted "
"source material to verify each assertion."
)
run.font.size = Pt(9)
run.font.italic = True
run.font.color.rgb = RGBColor(130, 130, 130)
doc.save(output_path)
return output_path
# ---------------------------------------------------------------------------
# CLI commands
# ---------------------------------------------------------------------------
def cmd_setup_check():
"""Check if all dependencies are available."""
checks = {
"PyMuPDF": False,
"Pillow": False,
"python-docx": False,
"Playwright": False,
"Chromium browser": False,
"Word (macOS)": False,
"LibreOffice": False,
}
try:
import fitz
checks["PyMuPDF"] = True
except ImportError:
pass
try:
from PIL import Image
checks["Pillow"] = True
except ImportError:
pass
try:
from docx import Document
checks["python-docx"] = True
except ImportError:
pass
try:
from playwright.sync_api import sync_playwright
checks["Playwright"] = True
except ImportError:
pass
# Check Chromium
playwright_cache = os.path.expanduser("~/Library/Caches/ms-playwright")
if not os.path.exists(playwright_cache):
playwright_cache = os.path.expanduser("~/.cache/ms-playwright")
if os.path.exists(playwright_cache) and any(
d.startswith("chromium") for d in os.listdir(playwright_cache)
):
checks["Chromium browser"] = True
# Check converters
if platform.system() == "Darwin" and os.path.exists("/Applications/Microsoft Word.app"):
checks["Word (macOS)"] = True
if shutil.which("libreoffice") or shutil.which("soffice"):
checks["LibreOffice"] = True
print("Eyeball dependency check:")
all_core = True
for name, ok in checks.items():
status = "OK" if ok else "MISSING"
marker = "+" if ok else "-"
print(f" [{marker}] {name}: {status}")
if name in ("PyMuPDF", "Pillow", "python-docx") and not ok:
all_core = False
has_converter = checks["Word (macOS)"] or checks["LibreOffice"]
has_web = checks["Playwright"] and checks["Chromium browser"]
print("")
print("Source support:")
print(f" PDF files: {'Ready' if all_core else 'Needs: pip3 install pymupdf pillow python-docx'}")
print(f" Word docs: {'Ready' if has_converter else 'Needs: Microsoft Word or LibreOffice'}")
print(f" Web URLs: {'Ready' if has_web else 'Needs: pip3 install playwright && python3 -m playwright install chromium'}")
return 0 if all_core else 1
def cmd_convert(args):
"""Convert a document to PDF."""
source = os.path.expanduser(args.source)
output = os.path.expanduser(args.output)
if source.startswith(("http://", "https://")):
render_url_to_pdf(source, output)
else:
convert_to_pdf(source, output)
print(f"Converted: {output} ({os.path.getsize(output)} bytes)")
def cmd_screenshot(args):
"""Generate a single screenshot from a PDF."""
pdf_doc = fitz.open(os.path.expanduser(args.source))
anchors = json.loads(args.anchors)
target_page = args.page
padding = args.padding or 40
img_bytes, page_label, size = screenshot_region(
pdf_doc, anchors,
target_page=target_page,
context_padding=padding,
dpi=args.dpi or 200
)
if img_bytes:
output = os.path.expanduser(args.output)
with open(output, "wb") as f:
f.write(img_bytes.getvalue())
print(f"Screenshot saved: {output} ({size[0]}x{size[1]}px, {page_label})")
else:
print(f"No matches found for: {anchors}", file=sys.stderr)
sys.exit(1)
pdf_doc.close()
def cmd_build(args):
"""Build a complete analysis document."""
source = os.path.expanduser(args.source)
output = os.path.expanduser(args.output)
sections = json.loads(args.sections)
title = args.title
subtitle = args.subtitle
# Determine source type and convert to PDF
with tempfile.NamedTemporaryFile(suffix=".pdf", delete=False) as tmp:
tmp_pdf = tmp.name
try:
if source.startswith(("http://", "https://")):
render_url_to_pdf(source, tmp_pdf)
source_label = source
elif source.lower().endswith(".pdf"):
shutil.copy2(source, tmp_pdf)
source_label = os.path.basename(source)
else:
convert_to_pdf(source, tmp_pdf)
source_label = os.path.basename(source)
pdf_doc = fitz.open(tmp_pdf)
build_analysis_doc(
pdf_doc, sections, output,
title=title, subtitle=subtitle,
source_label=source_label,
dpi=args.dpi or 200
)
pdf_doc.close()
size_kb = os.path.getsize(output) / 1024
print(f"Analysis saved: {output} ({size_kb:.0f} KB)")
finally:
if os.path.exists(tmp_pdf):
os.unlink(tmp_pdf)
def cmd_extract_text(args):
"""Extract text from a source document (for the AI to read before writing analysis)."""
source = os.path.expanduser(args.source)
with tempfile.NamedTemporaryFile(suffix=".pdf", delete=False) as tmp:
tmp_pdf = tmp.name
try:
if source.startswith(("http://", "https://")):
render_url_to_pdf(source, tmp_pdf)
elif source.lower().endswith(".pdf"):
shutil.copy2(source, tmp_pdf)
else:
convert_to_pdf(source, tmp_pdf)
pdf_doc = fitz.open(tmp_pdf)
for i in range(pdf_doc.page_count):
text = pdf_doc[i].get_text()
print(f"\n[PAGE {i+1}]")
print(text)
pdf_doc.close()
finally:
if os.path.exists(tmp_pdf):
os.unlink(tmp_pdf)
def main():
parser = argparse.ArgumentParser(
description="Eyeball: Document analysis with inline source screenshots"
)
sub = parser.add_subparsers(dest="command")
# setup-check
sub.add_parser("setup-check", help="Check dependencies")
# convert
p_conv = sub.add_parser("convert", help="Convert a document to PDF")
p_conv.add_argument("--source", required=True)
p_conv.add_argument("--output", required=True)
# screenshot
p_ss = sub.add_parser("screenshot", help="Generate a screenshot from a PDF")
p_ss.add_argument("--source", required=True, help="PDF file path")
p_ss.add_argument("--anchors", required=True, help="JSON array of search terms")
p_ss.add_argument("--page", type=int, help="Target page (1-indexed)")
p_ss.add_argument("--padding", type=int, default=40)
p_ss.add_argument("--dpi", type=int, default=200)
p_ss.add_argument("--output", required=True, help="Output PNG path")
# build
p_build = sub.add_parser("build", help="Build analysis document")
p_build.add_argument("--source", required=True,
help="Source document path or URL")
p_build.add_argument("--output", required=True,
help="Output .docx path")
p_build.add_argument("--sections", required=True,
help="JSON array of section objects")
p_build.add_argument("--title", help="Document title")
p_build.add_argument("--subtitle", help="Document subtitle")
p_build.add_argument("--dpi", type=int, default=200)
# extract-text
p_text = sub.add_parser("extract-text",
help="Extract text from a document (for AI analysis)")
p_text.add_argument("--source", required=True)
args = parser.parse_args()
if args.command == "setup-check":
sys.exit(cmd_setup_check())
elif args.command == "convert":
cmd_convert(args)
elif args.command == "screenshot":
cmd_screenshot(args)
elif args.command == "build":
cmd_build(args)
elif args.command == "extract-text":
cmd_extract_text(args)
else:
parser.print_help()
sys.exit(1)
if __name__ == "__main__":
main()