launchdarkly
Manage feature flags with LaunchDarkly. Use when a user asks to implement feature flags, roll out features gradually, do A/B testing, control feature access by user segment, or implement kill switches for features.
Best use case
launchdarkly is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Manage feature flags with LaunchDarkly. Use when a user asks to implement feature flags, roll out features gradually, do A/B testing, control feature access by user segment, or implement kill switches for features.
Teams using launchdarkly should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/launchdarkly/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How launchdarkly Compares
| Feature / Agent | launchdarkly | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Manage feature flags with LaunchDarkly. Use when a user asks to implement feature flags, roll out features gradually, do A/B testing, control feature access by user segment, or implement kill switches for features.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# LaunchDarkly
## Overview
LaunchDarkly is the industry-standard feature flag platform. Control feature rollouts, A/B tests, and entitlements without deploying new code. Supports gradual rollouts, targeting rules, and instant kill switches.
## Instructions
### Step 1: Setup
```bash
npm install @launchdarkly/node-server-sdk # server
npm install launchdarkly-react-client-sdk # React
```
### Step 2: Server-Side Flags
```typescript
// lib/flags.ts — Feature flag evaluation on the server
import * as LaunchDarkly from '@launchdarkly/node-server-sdk'
const client = LaunchDarkly.init(process.env.LAUNCHDARKLY_SDK_KEY!)
await client.waitForInitialization()
export async function getFlag(flagKey: string, user: { key: string; email?: string; plan?: string }) {
const context = {
kind: 'user',
key: user.key,
email: user.email,
custom: { plan: user.plan },
}
return client.variation(flagKey, context, false) // false = default
}
// Usage
const showNewDashboard = await getFlag('new-dashboard', { key: userId, plan: 'pro' })
if (showNewDashboard) {
return renderNewDashboard()
}
```
### Step 3: React Client
```tsx
// components/FeatureFlag.tsx — Client-side feature flags
import { withLDProvider, useFlags } from 'launchdarkly-react-client-sdk'
function App() {
const { newCheckout, darkMode } = useFlags()
return (
<div className={darkMode ? 'dark' : ''}>
{newCheckout ? <NewCheckout /> : <OldCheckout />}
</div>
)
}
export default withLDProvider({
clientSideID: process.env.NEXT_PUBLIC_LD_CLIENT_ID!,
context: { kind: 'user', key: userId, email: userEmail },
})(App)
```
### Step 4: Gradual Rollout
Configure in LaunchDarkly dashboard:
- **Percentage rollout**: 10% → 25% → 50% → 100% over days/weeks
- **Targeting rules**: enable for beta users first, then pro plan, then everyone
- **Kill switch**: instantly disable a feature if it causes issues
## Guidelines
- LaunchDarkly evaluates flags locally (SDK caches rules) — near-zero latency.
- Use multi-variate flags for A/B testing (not just boolean on/off).
- Pricing starts at $10/seat/month. For free alternative, consider Unleash (open-source).
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