By ananddtyagi
Track A/B tests and feature experiments across their lifecycle: proactively design setups with hypotheses and metrics when experiments start or change, monitor live performance, analyze results at milestones, and inform data-driven product decisions within 6-day development cycles.
Community-driven marketplace for Claude Code commands and plugins.
Add this marketplace to Claude Code:
/plugin marketplace add ananddtyagi/cc-marketplace
Then browse and install individual plugins (commands or agents):
/plugin
Install a specific command:
/plugin install lyra@cc-marketplace
Install a specific agent:
/plugin install accessibility-expert@cc-marketplace
Visit claudecodecommands.directory to:
Each plugin in this marketplace is independently installable:
/lyra, /audit, /ultrathink)Install only what you need - no bloat, full granular control!
This marketplace is automatically synced from the live database whenever commands are published or updated.
Individual commands may have their own licenses. See each command file for details.
Submit commands at claudecodecommands.directory/submit Submit agents at claudecodecommands.directory/submit-agent
Built with ❤️ by the Claude Code community
Uses power tools
Uses Bash, Write, or Edit tools
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Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
npx claudepluginhub ananddtyagi/claude-code-marketplace --plugin experiment-trackerSaaS Builder Guide - Build production-ready SaaS from design to deployment with 11 skill guides, 5 AI agents, and beginner-friendly FAQ
Perform security audit on codebase
Use this agent when you need to design, build, or validate n8n automation workflows. This agent specializes in creating efficient n8n workflows using proper validation techniques and MCP tools integration.\n\nExamples:\n- <example>\n Context: User wants to create a Slack notification workflow when a new GitHub issue is created.\n user: "I need to create an n8n workflow that sends a Slack message whenever a new GitHub issue is opened"\n assistant: "I'll use the n8n-workflow-builder agent to design and build this GitHub-to-Slack automation workflow with proper validation."\n <commentary>\n The user needs n8n workflow creation, so use the n8n-workflow-builder agent to handle the complete workflow design, validation, and deployment process.\n </commentary>\n</example>\n- <example>\n Context: User has an existing n8n workflow that needs debugging and optimization.\n user: "My n8n workflow keeps failing at the HTTP Request node, can you help me fix it?"\n assistant: "I'll use the n8n-workflow-builder agent to analyze and debug your workflow, focusing on the HTTP Request node configuration."\n <commentary>\n Since this involves n8n workflow troubleshooting and validation, use the n8n-workflow-builder agent to diagnose and fix the issue.\n </commentary>\n</example>\n- <example>\n Context: User wants to understand n8n best practices and available nodes for a specific use case.\n user: "What are the best n8n nodes for processing CSV data and sending email reports?"\n assistant: "I'll use the n8n-workflow-builder agent to explore the available nodes and recommend the best approach for CSV processing and email automation."\n <commentary>\n This requires n8n expertise and node discovery, so use the n8n-workflow-builder agent to provide comprehensive guidance.\n </commentary>\n</example>
Use this agent when handling customer support inquiries, creating support documentation, setting up automated responses, or analyzing support patterns. This agent excels at maintaining high-quality support across all studio projects while identifying product improvement opportunities. Examples:\n\n<example>\nContext: Setting up support for a new app launch
Use this agent when code changes have been made and you need to write new tests, run existing tests, analyze failures, and fix them while maintaining test integrity. This agent should be triggered proactively after code modifications to ensure comprehensive test coverage and suite health. Examples:\n\n<example>\nContext: The user has just implemented a new feature or modified existing code.\nuser: "I've updated the user authentication logic to support OAuth"\nassistant: "I've successfully updated the authentication logic. Now let me run the test-writer-fixer agent to ensure all tests pass with these changes."\n<commentary>\nSince code changes were made, use the Task tool to launch the test-writer-fixer agent to run relevant tests and fix any failures.\n</commentary>\n</example>\n\n<example>\nContext: The user has refactored a module or changed function signatures.\nuser: "Please refactor this payment processing module to use async/await"\nassistant: "I've completed the refactoring to use async/await throughout the payment module."\n<function call omitted for brevity>\nassistant: "Now I'll use the test-writer-fixer agent to run the tests and fix any issues caused by the refactoring."\n<commentary>\nAfter refactoring code, proactively use the test-writer-fixer agent to ensure tests still pass.\n</commentary>\n</example>\n\n<example>\nContext: The user has fixed a bug or made a critical change.\nuser: "Fix the race condition in the data synchronization service"\nassistant: "I've identified and fixed the race condition by implementing proper locking mechanisms."\n<function call omitted for brevity>\nassistant: "Let me run the test-writer-fixer agent to verify the fix doesn't break existing functionality."\n<commentary>\nAfter bug fixes, use the test-writer-fixer agent to ensure the fix works and doesn't introduce regressions.\n</commentary>\n</example>\n\n<example>\nContext: Code lacks test coverage for critical functionality.\nuser: "Our payment processing module has no tests"\nassistant: "That's a critical gap. Let me use the test-writer-fixer agent to create comprehensive tests for the payment module including edge cases and error scenarios."\n<commentary>\nCritical modules without tests are high-risk areas that need immediate test coverage.\n</commentary>\n</example>\n\n<example>\nContext: After implementing a new feature that needs tests.\nuser: "I've added the social sharing functionality"\nassistant: "Great! The social sharing is implemented. Now let me use the test-writer-fixer agent to write tests that ensure this feature works correctly across different platforms."\n<commentary>\nNew features should always include comprehensive test coverage from the start.\n</commentary>\n</example>
PROACTIVELY use this agent when experiments are started, modified, or when results need analysis. This agent specializes in tracking A/B tests, feature experiments, and iterative improvements within the 6-day development cycle. Should be triggered automatically when experimental code paths or feature flags are introduced. Examples:\n\n<example>\nContext: When implementing feature flags or A/B test variants\nuser: "Add a feature flag to test the new onboarding flow"\nassistant: "I've implemented the feature flag for the onboarding flow A/B test. Let me use the experiment-tracker agent to properly document this experiment and set up tracking."\n<commentary>\nEvery feature flag represents an experiment that needs proper tracking and success metrics.\n</commentary>\n</example>\n\n<example>\nContext: After deploying experimental features\nuser: "The new viral sharing feature is now live for 10% of users"\nassistant: "Great! The viral sharing feature is deployed. I'll use the experiment-tracker agent to monitor its performance and document initial results."\n<commentary>\nLive experiments need immediate tracking setup to capture valuable data from the start.\n</commentary>\n</example>\n\n<example>\nContext: When reaching experiment milestones\nuser: "It's been a week since we launched the TikTok integration test"\nassistant: "Perfect timing for analysis. Let me use the experiment-tracker agent to compile the week-one results and determine if we should expand the test."\n<commentary>\nRegular experiment checkpoints ensure data-driven decisions about feature rollouts.\n</commentary>\n</example>\n\n<example>\nContext: Before making product decisions\nuser: "Should we keep the AI avatar feature or remove it?"\nassistant: "Let me analyze the experiment data to inform this decision. I'll use the experiment-tracker agent to review all metrics and user feedback for the AI avatar feature test."\n<commentary>\nProduct decisions should be backed by experiment data, not gut feelings.\n</commentary>\n</example>
LaunchDarkly agent skills and MCP servers for feature flag management, AgentControl, and metrics
Claude Code skill pack for PostHog (24 skills)
Autonomous experiment loop that optimizes any file by a measurable metric. 5 slash commands, 8 evaluators, configurable loop intervals (10min to monthly).
DevsForge Enterprise Feature Flag Architect delivering comprehensive progressive rollout methodologies, A/B testing frameworks, canary deployment strategies, and experimentation platforms that transform risky releases into controlled, data-driven feature delivery systems
Access PostHog analytics, feature flags, experiments, error tracking, and insights directly from your AI coding tool. Optionally capture Claude Code sessions to PostHog LLM Analytics.