ph-algorithm-guide_skill

Overview

This skill explains how the Product Hunt ranking algorithm works and how to shape a launch strategy around known, publicly observed factors. It translates signals like vote weight, engagement depth, and velocity into concrete tactics you can apply on launch day. Use it to set realistic targets and reduce risk of algorithm penalties.

How this skill works

The skill inspects publicly reported algorithm behaviors and synthesizes them into actionable checks: vote quality, engagement patterns, timing/velocity, and account relationships. It models the daily cycle (randomized first 4 hours, then algorithmic ranking) and produces optimization recommendations and risk flags. Outputs focus on what to encourage (diverse, thoughtful engagement) and what to avoid (spikes, coordinated votes).

When to use it

• Planning a Product Hunt launch strategy
• Diagnosing unexpected rank changes during or after launch
• Designing outreach and supporter timing waves
• Preparing maker response and comment plans
• Setting realistic ranking and engagement targets

Best practices

• Prioritize quality over raw vote count — target established, active accounts
• Stagger supporter activity in multiple waves over 24 hours rather than all at once
• Encourage genuine comments and conversations, then respond quickly to build depth
• Diversify geographic and account-age sources to avoid clustering signals
• Avoid coordinated bulk voting, same-IP/device patterns, and obvious automation

Example use cases

• Create an engagement schedule with 4–6 supporter waves across the day
• Audit supporter list to estimate high-weight vs low-weight votes before launch
• Build a comment and maker-response plan to increase engagement depth
• Run a pre-launch risk checklist to catch geographic or timing clustering
• Estimate realistic rank ranges (conservative and optimistic) given expected vote quality