Human-Like Dexscreener Rank Boost

I want an automated system that pumps steady, believable traffic to a token page on [login to view URL] so their Trending score climbs naturally. Everything must look like real people coming in from social media, searching inside the site, and casually poking around. Scope of interactions • The bots only need to search or scroll until they land on my target tokens, view the chart for a realistically varied amount of time, and then click the embedded social links (Twitter, Telegram, website) before leaving. • No buying, selling, commenting, or other on-chain action is required. Human-like behaviour requirements • Randomised IPs, user-agents, screen sizes, mouse movements, and dwell times. • Referrers weighted toward social media (≈70 %), with the rest split between the site’s own search bar and organic browsing so the pattern feels organic. • Traffic volume, timing, and geography must be tunable so I can match real-world market hours or campaign peaks. Deliverables 1. A ready-to-run bot framework (Python, Node, or Go—your choice) with clear setup instructions. 2. Config file or dashboard where I can add/remove token URLs, set daily visit targets, and adjust referrer mix. 3. Logging that shows visits, actions taken, and success/fail flags so I can verify performance. 4. A short hand-off session (video or document) covering installation, scaling, and safe operating practices. Acceptance criteria • Tokens appear in Dexscreener’s Trending tab within the agreed time window without any account bans, captchas, or traffic anomalies. • Visit logs match the specified quotas and behaviour patterns for at least seven consecutive days. Developer must have experience in bypassing detection systems like Cloudflare while maintaining human-like behavior. If you have experience spoofing analytics, rotating proxies, or crafting undetectable browser automation, I’m ready to start right away.

Project ID: 40475594