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 travisjneuman/.claude --skill growth-engineeringgit clone --depth 1 https://github.com/travisjneuman/.claudeWrote 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/travisjneuman/.claude/growth-engineering)<a href="https://agentmods.dev/skills/travisjneuman/.claude/growth-engineering"><img src="https://agentmods.dev/badge/skills/travisjneuman/.claude/growth-engineering/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/travisjneuman/.claude/growth-engineering"><img src="https://agentmods.dev/badge/skills/travisjneuman/.claude/growth-engineering.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 166 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 168 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00047 | $0.01119 |
| Opus 5.5 | $0.00019 | $0.00448 |
| Sonnet 5.5 | $0.00009 | $0.00224 |
| Haiku 4.5 | $0.00005 | $0.00112 |
Grade A, and why
growth-engineering 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 1mo 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Growth Engineering Skill
Infrastructure and patterns for product-led growth, experimentation, and conversion optimization.
Feature Flag Systems
Implementation Pattern
// lib/feature-flags.ts
import { PostHog } from 'posthog-node';
const posthog = new PostHog(process.env.POSTHOG_API_KEY!);
interface FeatureFlags {
'new-onboarding-flow': boolean;
'pricing-experiment': 'control' | 'variant-a' | 'variant-b';
'ai-suggestions': boolean;
}
export async function getFlag<K extends keyof FeatureFlags>(
key: K,
userId: string,
): Promise<FeatureFlags[K]> {
const value = await posthog.getFeatureFlag(key, userId);
return value as FeatureFlags[K];
}
// Usage in component
const showNewOnboarding = await getFlag('new-onboarding-flow', user.id);
Feature Flag Best Practices
- Short-lived flags: Remove after experiment concludes (< 2 weeks)
- Long-lived flags: Ops toggles for gradual rollouts, kill switches
- Never nest feature flags (creates exponential complexity)
- Clean up stale flags monthly
- Log flag evaluations for debugging
A/B Testing Infrastructure
Experiment Design
// lib/experiments.ts
interface Experiment {
id: string;
name: string;
variants: {
id: string;
weight: number; // 0-100, must sum to 100
}[];
targetAudience: {
percentage: number; // % of users included
filters?: Record<string, unknown>;
};
primaryMetric: string;
secondaryMetrics: string[];
minimumSampleSize: number;
startDate: Date;
endDate?: Date;
}
// Track experiment exposure
function trackExposure(experimentId: string, variantId: string, userId: string) {
analytics.capture({
event: '$experiment_started',
distinctId: userId,
properties: {
$experiment_id: experimentId,
$variant_id: variantId,
},
});
}
Statistical Significance
- Minimum sample size: Calculate before starting (use Evan Miller calculator)
- Don't peek: Set duration upfront, don't stop early on promising results
- Sequential testing: Use if you must check early (adjusts p-values)
- Minimum detectable effect: Define what improvement matters (e.g., 5% lift)
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.
- 1mo ago Changed c9f2d1658759
- 2mo ago First seen · 173 lines · 47 tokens per session scan A ce8a35a7aa8d
growth-engineering is a skill published in the GitHub repository travisjneuman/.claude (108 stars, last pushed yesterday), licensed MIT. It adds 47 tokens to every session and 1,119 once invoked, about $0.0002 per session on Opus 5.5. 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.
growth-engineering compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| growth-engineeringtravisjneuman/.claude | Skill | 108 | yesterday | MIT | A | 47 | Claude Code |
| imagegenopenai/codex | Skill | 135k | today | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 100k | today | Apache-2.0 | A | 19 | Claude Code |
| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 316k | 7d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |