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Feature Flags and Experimentation

Automates feature flag rollouts, A/B tests, and targeting rules across software systems.

Updated Aug 23, 2026
Search Tags:#A/B testing#feature flags#experimentation#canary#rollout#targeting#LaunchDarkly
One-click install
npx skills add https://github.com/qenex-ai/devops-plugin --skill feature-flags-and-experimentation
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Feature Flags and Experimentation
Source: https://github.com/qenex-ai/devops-plugin/tree/main/skills/feature-flags-experimentation
Command: npx skills add https://github.com/qenex-ai/devops-plugin --skill feature-flags-and-experimentation

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Managing feature exposure and experimentation across software platforms is error-prone and slow. This Skill provides a centralized approach to enable/disable features, run A/B tests, and orchestrate gradual rollouts with clear rules and telemetry.

Core Features & Use Cases

  • Feature flag evaluation & rollout control: Gate new features behind flags with percent-based rollouts and audience targeting.
  • Experimentation configuration & analytics integration: Define experiments with variants, weights, and metrics; track exposures and conversions.
  • Use Case: A/B test a new checkout flow on web and mobile, gradually exposing it to users based on their segment and then measuring impact.

Quick Start

Enable the 'checkout_flow_beta' flag for internal testers and create an experiment with two variants: control and treatment.

Frequently Asked Questions about Feature Flags and Experimentation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up a gradual rollout for a new feature flag?▼

Run A/B tests by defining experiments with multiple variants, traffic weights, and tracking metrics. The system evaluates variants server-side or via client-side SDKs, tracking exposures and conversions to measure impact like a checkout flow test.

Can I use LaunchDarkly with my existing custom backend for experimentation?▼

Yes, LaunchDarkly is supported alongside Unleash and custom backends. The system integrates with these platforms to manage experimentation decisions, apply targeting rules, and synchronize feature flag states across your software systems.

What is server-side evaluation for feature flags?▼

Server-side evaluation determines feature flag variants and rollout states within your backend services. This approach prevents client-side exposure of targeting rules and ensures consistent experimentation decisions across web and mobile platforms.

How do I configure targeting rules for a canary release?▼

Configure canary releases by applying audience targeting rules to feature flags, restricting exposure to specific user segments. This allows you to gate new features for internal testers or specific groups before a full rollout.

Does this approach work for A/B testing across both web and mobile platforms?▼

Yes, feature flag management and experimentation decisions apply across web, mobile, and backend services. You can A/B test a new checkout flow simultaneously on both platforms using client-side SDKs and server-side evaluation.

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