# Agent Types HyperCognition supports a wide variety of agent archetypes, each tailored to different user needs, risk profiles, and market conditions. Every agent is backed by a wallet, a strategy engine, and HyperMind's cognition. ### **1. Alpha Agents** * Objective: Identify short-term alpha across chains (e.g. new token launches, trending pairs, pump cycles) * Tactics: Sentiment scraping, memecoin radar, token velocity scans * Users: High-risk traders, early-mover degens ### **2. Yield Agents** * Objective: Optimize stable yield across DeFi protocols * Tactics: LP routing, vault rotation, lending APY arbitrage, auto-compounding * Users: Passive income seekers, DAO treasuries, long-term holders ### **3. Perp Agents** * Objective: Execute leveraged strategies on perpetual DEXs (e.g. Hyperliquid, GMX, etc.) * Tactics: Trend following, volatility spikes, liquidation hunting, basis trades * Users: Experienced traders, volatility chasers ### **4. Arbitrage Agents** * Objective: Exploit inefficiencies across pools, bridges, oracles * Tactics: Triangular arb, bridge latency arb, stablecoin depeg detection * Users: Institutional users, low-risk capital deployers ### **5. Social Agents** * Objective: Mirror strategies of top-performing wallets, DAOs, or influencers * Tactics: Smart wallet tracking, copy-trading, sentiment mirroring * Users: Beginners, fans of KOLs, community-focused users ### **6. Custom Agents** * Objective: Built by users using agent templates or from scratch * Tactics: Anything programmable: narrative plays, vesting snipes, sector rotations * Users: Developers, advanced DeFi strategists, alpha groups --- # 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://whitepaper.hypercognition.io/hypercognition/agent-types.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.