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experiment-tracker

v1.0.0

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>

Claude Code

By Michael Galpert945 GitHub starsUpdated last month

Directory evidence

Runtimes
Claude Code
Parsed components
0 skill or MCP entries
Source updated
Aug 12, 2026
Manifest status
Canonical path parsed

The directory validates manifest shape and source location. It does not execute the plugin or provide a security endorsement. Review the indexing methodology →

Install experiment-tracker for Claude Code

Installs for the current user
claude plugin marketplace add IchenDEV/agent-plugin-mkt
claude plugin marketplace update agent-plugin-marketplace
claude plugin install experiment-tracker-2@agent-plugin-marketplace

Paste and run these commands in a terminal with Claude Code. They add and refresh the PluginsMP catalog, then install this plugin.

The installer fetches third-party code from the source repository shown on this page. This directory validates manifest structure and source location, but does not perform a security audit; review the manifest, components, and source before installing.

Get the source manually
git clone https://github.com/ccplugins/awesome-claude-code-plugins

Clone the source repository, then follow its setup instructions to add the plugin to a compatible client. The plugin root is plugins/experiment-tracker/.

Plugin files

plugins/experiment-tracker/
└── .claude-plugin/plugin.json

Plugin manifests1

plugins/experiment-tracker/.claude-plugin/plugin.json
{
  "name": "experiment-tracker",
  "description": "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>",
  "version": "1.0.0",
  "author": {
    "name": "Michael Galpert"
  },
  "homepage": "https://github.com/ccplugins/awesome-claude-code-plugins/tree/main/plugins/experiment-tracker"
}

For maintainers

If you maintain this plugin, link to this source-backed listing from your README so users can review its manifest and indexed components.

[experiment-tracker on Agent Plugins Marketplace](https://pluginsmp.com/plugins/experiment-tracker-2)