Human-Like Dexscreener Rank Boost

I want an automated system that pumps steady, believable traffic to a token page on Dexscreener.com 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.