Twinify

Create AI digital twins of real people from WhatsApp chat history exports. Clone your friends, colleagues, or contacts into AI agents that talk, think, and react like them. Use when the user wants to: create a digital twin, clone a WhatsApp contact into an AI agent, build a persona from chat history, make an AI version of someone, create a doppelgänger agent, or simulate a conversation with someone based on their real messages. Triggers: digital twin, clone friend, chat clone, persona, doppelgänger, twin agent, AI clone, simulate person, WhatsApp clone, chat personality, mimic friend. Important: Requires explicit consent from the person being cloned. Always confirm permission before proceeding.

This skill appears to do what it says: parse local WhatsApp exports and generate profile files for a persistent OpenClaw agent. Before installing or running it: - Confirm you have explicit, informed consent from the person whose chats you will use (the SKILL.md emphasizes this). Unauthorized use is a serious privacy and ethical risk. - Inspect the generated files and any config patch (gateway config.patch) before applying it — ensure it only registers the new agent and does not alter unrelated agents or global settings. - Keep the workspace secure (permissions/encryption) because parsed messages and persona files contain sensitive personal data. Delete all workspace files if the subject withdraws consent. - Verify how your LLM provider is configured on this platform so you understand whether any data is sent to external services and what logging/retention policies apply. - If you need higher assurance, run the parser on a sanitized sample and manually review outputs before creating a real twin. Given the privacy sensitivity, proceed only after confirming consent and reviewing the files/config changes the skill will make.

Type: OpenClaw Skill Name: twinify Version: 1.0.0 This skill is classified as suspicious due to its inherent high-risk data handling capabilities. It processes highly sensitive personal WhatsApp chat history and explicitly states in `SKILL.md` that this data will be transmitted to an external LLM API for analysis. While the skill includes ethical instructions for the agent to confirm user consent and the `scripts/parse_chat.py` file itself does not contain malicious code or unauthorized network activity, the fundamental operation of sending private chat data to a third-party LLM constitutes a significant privacy risk, even if it's aligned with the stated purpose. No evidence of intentional malicious behavior (e.g., unauthorized exfiltration, persistence, or prompt injection against the agent for harmful objectives) was found.