Answer patient enquiries for a clinic by chat
An n8n and Gemini agent receives patient chat messages, keeps context, uses clinic info from Google Sheets and responds to enquiries.
The author built an open-source contract-review skill for Claude Code and other AI coding tools to review NDAs, SaaS agreements, vendor terms and merchant agreements.
The author built an open-source contract-review skill for Claude Code and other AI coding tools to review NDAs, SaaS agreements, vendor terms and merchant agreements.
The author packaged a contract-review skill as an open-source Claude Code add-on with a one-line install from GitHub into the local skills folder. They describe using it inside their workflow to review NDAs, SaaS agreements, vendor terms, and merchant agreements, and the thread positions it as usable with Claude Code and similar AI coding tools rather than a fully autonomous service.
The stated result is a free, open-source review skill shared publicly on Reddit and GitHub for contract checking across several common agreement types. The thread excerpt does not give performance numbers, examples of detected issues, or a comparison against lawyer review.
The main practical catch mentioned is setup: installation is a local git clone into ~/.claude/skills/contract-review; the available thread excerpt gives no cost or time figures.
I have a contract at [file path], which is a [NDA, SaaS agreement, vendor terms, etc.]. I am the [party, e.g. customer or vendor]. Read it clause by clause and flag risky or unusual terms such as liability caps, auto-renewal, IP ownership, termination and indemnity. Finish with a table of issues ranked by severity, with suggested redline language for each. Do not edit the original file, and remind me you are not a lawyer.
An n8n and Gemini agent receives patient chat messages, keeps context, uses clinic info from Google Sheets and responds to enquiries.
An n8n workflow has AI classify web-form jobs by type, urgency and summary, create an Airtable record, reply instantly and flag uncertain cases.
Lindy agents summarized meeting notes, sent action items to teammates, suggested knowledge-base replies on support tickets, and handled follow-up emails and calendar updates.