Contract Analysis and Risk Scoring
Upload a PDF contract to get a plain English translation, a 0-100 risk score, and an HTML email report of hidden traps.
What it does
Upload your PDF contract to instantly receive a plain English translation, a 0-100 risk score, and an email report highlighting hidden traps. You get these insights compiled into a clear HTML summary without needing to decipher complex legal jargon yourself.
Step by step
- Parse the uploaded PDF to extract raw text content for processing.
- Send the file hash or binary payload to VirusTotal API and wait for scan completion status.
- Format the final output into an HTML template with sections for translation and risk breakdown.
Where the LLM does the work
- Use Anthropic to summarize complex legal clauses into plain English without losing key obligations.
- Prompt OpenAI to evaluate specific contract terms against a defined risk rubric and assign a numerical score.
- Synthesize the translated text and risk scores into a coherent narrative summary for the report.
Watch out for
Gmail API quotas are strict for new accounts, so queue emails or use batch sending if processing multiple contracts simultaneously.
Different PDF structures can break text extraction, so test with various document layouts and handle empty fields gracefully.
Tools that fit
Anthropic Chat Model LLM Legal translation to plain English
OpenAI Chat Model LLM Risk scoring and trap detection
HTTP Request API VirusTotal malware scanning
The agent brief
Everything your agent needs, including the gotchas. Copy it and go.
You are helping me build the following AI agent workflow. ## Goal Contract Analysis and Risk Scoring: Upload a PDF contract to get a plain English translation, a 0-100 risk score, and an HTML email report of hidden traps. ## Specification - What it does: Upload your PDF contract to instantly receive a plain English translation, a 0-100 risk score, and an email report highlighting hidden traps. You get these insights compiled into a clear HTML summary without needing to decipher complex legal jargon yourself. - Trigger: Run manually (Manual · on new contract upload) - Autonomy: Fully hands-off - Expected setup effort: about an afternoon - Tools/services involved: - Anthropic Chat Model: Legal translation to plain English - OpenAI Chat Model: Risk scoring and trap detection - Gmail: Sending analysis report email - HTTP Request: VirusTotal malware scanning ## Known pitfalls, handle each one explicitly in your implementation 1. Gmail API quotas are strict for new accounts, so queue emails or use batch sending if processing multiple contracts simultaneously. 2. Different PDF structures can break text extraction, so test with various document layouts and handle empty fields gracefully. ## Reference implementation https://n8n.io/workflows/14659 (workflow template) Fetch and inspect this before building. If it matches my stack, adapt it; if not, rebuild the pattern with my tools. ## Process requirements 1. Before building: ask me which of the listed tools I actually use and what my platform is (n8n / Make / code / other). Do not assume. 2. Adapt the pattern to my answers; do not force the reference stack. 3. Address every pitfall above; tell me how you handled each. 4. Provide a test plan I can run before letting this touch real data. 5. Ask before any step that sends messages, modifies data, or spends money. Source: https://usecasesforagents.com/use-case/contract-analysis-and-risk-scoring/ via usecasesforagents.com
Frequently asked questions
Can I use a different LLM than Anthropic?
Yes. Anthropic is only the example LLM in this recipe. The same flow works with Cohere, DeepSeek, Google Gemini and Google Vertex AI. Swap the LLM connection and keep the rest of the setup as written.
Want this running in your business?
This is what I do. I design and build AI agents like this one, and keep them running. If you want it set up for your team instead of doing it yourself, get in touch.
Who it's for
Built for freelancers and consultants juggling this across every client, not just one.
Also fits E-commerce Operator.
Works just as well for personal use, no business context needed.