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 SkeneTechnologies/plg-skills --skill growth-experimentationgit clone --depth 1 https://github.com/SkeneTechnologies/plg-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/skenetechnologies/plg-skills/growth-experimentation)<a href="https://agentmods.dev/skills/skenetechnologies/plg-skills/growth-experimentation"><img src="https://agentmods.dev/badge/skills/skenetechnologies/plg-skills/growth-experimentation/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/skenetechnologies/plg-skills/growth-experimentation"><img src="https://agentmods.dev/badge/skills/skenetechnologies/plg-skills/growth-experimentation.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00085 | $0.03394 |
| Opus 5 | $0.00043 | $0.01697 |
| Sonnet 5 | $0.00017 | $0.00679 |
| Haiku 4.5 | $0.00009 | $0.00339 |
Grade A, and why
growth-experimentation 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 12d 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 — 373 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Growth Experimentation
You are a growth experimentation specialist. Build a high-velocity experimentation practice that systematically discovers what drives growth. This skill covers experiment types, hypothesis design, prioritization frameworks, statistical foundations, analysis, and building an experimentation culture.
Diagnostic Questions
Before designing experiments, clarify:
- What is your monthly active user count? (Determines statistical power and what you can test)
- What is your current experiment velocity? (Experiments per month)
- Do you have an experimentation platform? (Feature flags, A/B testing tool)
- Who runs experiments? (Dedicated growth team, product teams, everyone?)
- What are your top 3 growth levers? (Where should experiments focus?)
- How do you currently make product decisions? (Data-driven, intuition, HiPPO?)
- What is your risk tolerance? (Can you tolerate temporary conversion drops during testing?)
Experiment Types
| Type | What | When to Use | Traffic Needed |
|---|---|---|---|
| A/B Test | Two variants, randomly assigned | Sufficient traffic, clear metric, need statistical confidence | 1,000+ conversions per variant |
| Multivariate (MVT) | Multiple variables simultaneously | Understand interaction effects. Only with very high traffic | Much higher than A/B |
| Feature Flag / Progressive Rollout | Release to small %, gradually increase | New feature launches with risk mitigation | N/A (no statistical rigor needed) |
| Phased Rollout | Internal -> beta -> 10% -> 25% -> 50% -> 100% | Major launches with high risk | Monitor guardrails at each phase |
| Fake Door Test | Show non-existent feature, measure click rate | Validate demand before building | Low (measuring interest only) |
| Holdout Test | Keep 5-10% on old experience permanently | Measuring long-term cumulative impact | Months of duration |
Hypothesis Framework
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.
- 12d ago First seen · 373 lines · 85 tokens per session scan A d6bee46347c2
growth-experimentation is a skill published in the GitHub repository SkeneTechnologies/plg-skills (19 stars, last pushed 7mo ago), licensed MIT. It adds 85 tokens to every session and 3,394 once invoked, about $0.0004 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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