Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add yoanbernabeu/producthunt-skills --skill ph-algorithm-guidegit clone --depth 1 https://github.com/yoanbernabeu/producthunt-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/yoanbernabeu/producthunt-skills/ph-algorithm-guide)<a href="https://agentmods.dev/skills/yoanbernabeu/producthunt-skills/ph-algorithm-guide"><img src="https://agentmods.dev/badge/skills/yoanbernabeu/producthunt-skills/ph-algorithm-guide.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00031 | $0.01766 |
| Opus 5 | $0.00015 | $0.00883 |
| Sonnet 5 | $0.00006 | $0.00353 |
| Haiku 4.5 | $0.00003 | $0.00177 |
Grade A, and why
ph-algorithm-guide scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 339 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Hunt Algorithm Guide
This skill explains how Product Hunt's ranking algorithm works, helping you optimize your launch strategy based on publicly known factors.
When to Use This Skill
- Planning your launch strategy
- Understanding why rankings change
- Optimizing for algorithm factors
- Diagnosing ranking issues
- Setting realistic expectations
Algorithm Fundamentals
Key Insight
Upvotes ≠ Points
Product Hunt CTO Mike Kerzhner confirmed: "There is not a 1:1 correspondence between upvotes and points."
What This Means
- Not all votes count equally
- Account quality matters
- Engagement quality matters
- Timing patterns matter
Known Ranking Factors
Factor 1: Vote Weight
Higher Weight Votes:
- Older accounts (months/years old)
- Active accounts (regular engagement)
- Diverse activity (not just voting)
- Organic voting pattern
Lower Weight Votes:
- New accounts (recently created)
- Inactive accounts (created but unused)
- Single-purpose accounts
- Suspicious patterns
Potentially Discounted:
- Brand new accounts
- Accounts created same day
- Bulk votes from same source
- Coordinated voting patterns
Factor 2: Engagement Depth
Positive Signals:
- Thoughtful comments
- Discussion threads
- Maker responses
- Question-answer exchanges
Why It Matters:
- Comments indicate genuine interest
- Discussions show community value
- Engagement harder to fake than votes
Factor 3: Velocity Pattern
What Algorithm Watches:
- Rate of upvote accumulation
- Time distribution of votes
- Spikes vs steady growth
- Natural vs artificial patterns
Healthy Pattern:
Hour 1: [████████░░] 40 votes
Hour 2: [██████░░░░] 35 votes
Hour 3: [███████░░░] 38 votes
Hour 4: [█████████░] 45 votes
Suspicious Pattern:
Hour 1: [██████████] 150 votes (spike!)
Hour 2: [█░░░░░░░░░] 5 votes
Hour 3: [█░░░░░░░░░] 3 votes
Hour 4: [█░░░░░░░░░] 2 votes
Factor 4: First 4 Hours
Special Period:
- Rankings randomized initially
- Vote counts hidden publicly
- Algorithm observing patterns
- Critical for initial position
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 339 lines · 31 tokens per session scan A fa68ce9aba2f
ph-algorithm-guide is a skill published in the GitHub repository yoanbernabeu/producthunt-skills (18 stars, last pushed 7mo ago), licensed MIT. It adds 31 tokens to every session and 1,766 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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