Eyeball

# 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:

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:

python3 <path-to>/eyeball.py setup-check

If anything is missing, install the required dependencies:

pip3 install pymupdf pillow python-docx playwright
python3 -m playwright install chromium

On Windows, also install pywin32 for Word automation:

pip install pywin32

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:

python3 <path-to>/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:

{"anchors": ["User-Generated Content"], "target_page": 8}

RIGHT -- uses the specific language that supports the claim:

{"anchors": ["retain ownership", "Ownership of Content, Right to Post"], "target_page": 8}

WRONG -- section title appears as a cross-reference on earlier pages:

{"anchors": ["LIMITATION OF LIABILITY"]}

RIGHT -- includes the section number for precision, targets the correct page:

{"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:

python3 <path-to>/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...",