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 deciqAI/knowledge-skills --skill k-factor-viralgit clone --depth 1 https://github.com/deciqAI/knowledge-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/deciqai/knowledge-skills/k-factor-viral)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/k-factor-viral"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/k-factor-viral/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/k-factor-viral"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/k-factor-viral.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00110 | $0.01840 |
| Opus 5 | $0.00055 | $0.00920 |
| Sonnet 5 | $0.00022 | $0.00368 |
| Haiku 4.5 | $0.00011 | $0.00184 |
Grade A, and why
k-factor-viral 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 9d 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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
K-Factor and Viral Coefficient
Overview
K = i × c, where i = average invites per existing user, c = conversion rate into new activated users. K > 1 → exponential growth; K < 1 → finite ceiling; K = 1 → linear. Most "viral" products have K in the 0.1-0.6 range — social transmission, not a growth engine.
Codified by Steve Jurvetson (DFJ) via the Hotmail case (1996); formalized by Andrew Chen, David Skok, and early Facebook/LinkedIn growth teams.
Composes with aarrr-pirate-metrics (K sits in Referral), network-effects (value vs. user count — different things), mvp (smoke tests cannot establish K), feedback-loops (K > 1 is a specific reinforcing-loop condition).
When to Use
- A product is described as "viral" without an explicit K calculation
- Growth plateauing despite "viral elements" (share buttons, referral programs, invite flows)
- A growth team debating which lever to pull without the K = i × c decomposition
- An investor or founder using "viral" to justify a growth forecast
- Not when: B2B enterprise; focus is engagement/retention; pre-PMF product
Coaching Novices (Adaptive Front Door)
- Engine mode: user has a concrete case → run The Process directly.
- Coach mode: user unfamiliar or no concrete case → guide step by step.
In Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.
- One-line: virality is K = i × c > 1 — below 1, the product doesn't grow by itself.
- Check fit: B2B / enterprise / pre-PMF → not this lens yet.
- Elicit the product and current invite mechanic.
[WAIT — do not advance until user responds]
- One question at a time: what's i? what's c? what's K? is K stable across waves?
[WAIT — do not advance until user responds]
- Close: name the specific i lever or c lever to attack.
[WAIT — do not advance until user responds]
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 123 lines · 110 tokens per session scan A d51c3e4bfc65
k-factor-viral is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 10d ago), licensed MIT. It adds 110 tokens to every session and 1,840 once invoked, about $0.0006 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 2026-09-03.
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