growth-engineering

growth-engineering is a skill for Claude Code, Codex from travisjneuman/.claude. It costs 47 tokens per session (1,124 once invoked), scanned A, original, MIT.

A guide to product growth engineering: using feature flags, controlled A/B tests, and funnel analysis to learn which product changes improve user actions. A feature flag is a switch that shows a feature to selected users without deploying separate code versions.

In plain words
What is it for?
Use it to build experimentation systems, manage feature toggles, run A/B tests, and optimize conversion funnels.
Why use it?
It helps teams release changes gradually, compare variants, and measure where users stop in a signup or purchase journey. This makes product decisions easier to test with user behavior.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: reads .claude/ paths.

Good fit Use it to build experimentation systems, manage feature toggles, run A/B tests, and optimize conversion funnels.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/travisjneuman/.claude/growth-engineering
Install

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.

Any agent
npx skills add travisjneuman/.claude --skill growth-engineering
Clone the repo
git clone --depth 1 https://github.com/travisjneuman/.claude

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for growth-engineering

README.md
[![agentmods](https://agentmods.dev/badge/skills/travisjneuman/.claude/growth-engineering/github.svg)](https://agentmods.dev/skills/travisjneuman/.claude/growth-engineering)
Your own site
<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.

agentmods 80×15 button for growth-engineering

Your own site · 80×15
<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>
Per session 47 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,124 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
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.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00047 $0.01124
Opus 5 $0.00023 $0.00562
Sonnet 5 $0.00009 $0.00225
Haiku 4.5 $0.00005 $0.00112

Measured 9d ago against content hash ce8a35a7aa8d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

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 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.

skills/growth-engineering/SKILL.md · 173 lines

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)

Read the full file on GitHub · 173 lines

Changes

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.

  1. 9d ago First seen · 173 lines · 47 tokens per session scan A ce8a35a7aa8d

Subscribe to this mod's changes

growth-engineering is a skill published in the GitHub repository travisjneuman/.claude (97 stars, last pushed 7d ago), licensed MIT. It adds 47 tokens to every session and 1,124 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 2026-09-03.

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