# Launcher Chat Your launcher assistant that lets users configure, launch, and manage tokens entirely through natural language conversation. It replaces forms and dashboards with a single conversational interface. **What it does** 1. **Token configuration** - Users describe what they want ("launch a token called DROME, 1 billion supply, V2 pool paired with WETH, 0.5 ETH liquidity") and Chat builds the full launch configuration in real time. Every parameter from name, symbol, supply, pool type, pair token, initial liquidity, to lock duration can be set, reviewed, and modified through conversation before committing to deployment. 2. **One-click launch from chat** - Once the configuration is finalized, Chat presents a summary card with all parameters. The user confirms and signs the transaction directly from the chat interface. The full launch sequence - token deployment, pool creation, liquidity seeding, and LP locking - executes exactly as it would through the manual Launch page. 3. **Position monitoring** - After deployment, users can ask Chat about their tokens: pool address, current price, holder count, claimable trading fees, and AERO emission status. Chat queries onchain data and the Reflect backend to return live information without the user needing to navigate to the Token Management dashboard. 4. **Aerodrome guidance** - Chat understands Aerodrome mechanics and can answer questions about pool types (V2 vs Concentrated Liquidity), gauge graduation requirements, veAERO voting dynamics, fee structures, and LP locking. It acts as a knowledge base for users who are new to the Aerodrome ecosystem. Chat runs on Venice AI (llama-3.3-70b) --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.reflect.now/launcher/launcher-chat.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.