eyeball
Helps your agent document analysis with screenshots. Every claim in an analyzed document will have a source screenshot for easy verification.
What it does
Eyeball analyzes documents and creates a Word file. Every claim in the document has a screenshot from the original source with the exact text highlighted, so you can verify it.
When to use it
- ✓When you want to be sure that the information in a document is true.
- ✓When reviewing a contract and needing to confirm specific clauses.
- ✓When studying an article and wanting to see where the facts came from.
Example of what to ask your AI
“Analyze this PDF and show me where the information about liability is.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
It reads the document you provide, identifies important claims, and finds the exact snippet in the original source. Then, it creates a new document with these claims and screenshots for you to check.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add github/awesome-copilot --skill eyeballOr download just the file:
curl -L https://raw.githubusercontent.com/github/awesome-copilot/main/skills/eyeball/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
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:
- Reference the correct section number as it appears in the document (e.g., "Section 9" not "Section 8" because you assumed the numbering).
- Reference the correct page number where the section appears in the extracted text.
- 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...",
"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 documentanalysis(required): Your analysis text
…
FAQ
What are 'anchors'?
They are exact snippets from the original text that the AI uses to find the information and generate the screenshot.
What happens if the AI can't find the exact text?
The final document will state that the snippet was not found. Either the exact text isn't in the source, or the 'anchor' used wasn't precise enough.
Can I use Eyeball with web pages?
Yes, it works with web page links, as well as Word and PDF files.
Details
Original description by the author
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.
repo: github/awesome-copilot
Popularity
- GitHub stars
- 40k
- Ranking position
- #5137
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
More skills from this repository
acquire-codebase-knowledge
Helps your agent understand and document an existing code project. It's useful for onboarding new people or getting an overview of the architecture.
github/awesome-copilot
acreadiness-assess
Enables your agent to assess a project's readiness for AI and generate a report. It's useful for understanding how well a project is prepared to use AI tools.
github/awesome-copilot
acreadiness-generate-instructions
Helps your agent create instructions for AI tools based on an assessment. It's useful for improving how AI interacts with code and closing identified gaps.
github/awesome-copilot
acreadiness-policy
Enables your agent to help define or apply policies for AI project assessment. It's useful for standardizing how projects are evaluated and ensuring compliance.
github/awesome-copilot
Similar skills
architecture-decision-records
Has your agent record important project structure decisions. It helps to understand the reasoning behind choices and maintain a clear history of changes.
affaan-m/ECC
code-tour
Lets your agent create step-by-step code walkthroughs with exact file and line anchors. It's useful for project introductions, code explanations, or change reviews. Helps understand how a system works.
affaan-m/ECC
codebase-onboarding
Helps your agent analyze unfamiliar code and create an onboarding guide. It includes an architecture map, entry points, and conventions. Ideal for starting on a new project.
affaan-m/ECC