45 lines
3.4 KiB
JSON
45 lines
3.4 KiB
JSON
{
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"$schema": "internal://schemas/plugin.lock.v1.json",
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"pluginId": "gh:ananddtyagi/claude-code-marketplace:plugins/experiment-tracker",
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"normalized": {
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"repo": null,
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"ref": "refs/tags/v20251128.0",
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"commit": "c658fbe61d965c1b675aeb9b260baa3a606d3ffa",
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"treeHash": "8a241e8bc02a1087de7cec71f7438e76ed60fed8ef5577138ed5c0c322d71fab",
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"generatedAt": "2025-11-28T10:13:30.927007Z",
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"toolVersion": "publish_plugins.py@0.2.0"
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},
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"origin": {
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"remote": "git@github.com:zhongweili/42plugin-data.git",
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"branch": "master",
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"commit": "aa1497ed0949fd50e99e70d6324a29c5b34f9390",
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"repoRoot": "/Users/zhongweili/projects/openmind/42plugin-data"
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},
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"manifest": {
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"name": "experiment-tracker",
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"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>",
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"version": "1.0.0"
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},
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"content": {
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"files": [
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{
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"path": "README.md",
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"sha256": "c537019ad46a2e27740c63e02ffc15635a5b2f259f92f97f92dce4cf3c839109"
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},
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{
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"path": "agents/experiment-tracker.md",
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"sha256": "dcbce15cdbad85f334cfa96f8554316c8e5756ebae19061813ef808bd7cee7df"
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},
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{
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"path": ".claude-plugin/plugin.json",
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"sha256": "b1f947a4be950468a3d57e7daa716695b00232d81fac7080a2e2f9a22d772acc"
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}
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],
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"dirSha256": "8a241e8bc02a1087de7cec71f7438e76ed60fed8ef5577138ed5c0c322d71fab"
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},
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"security": {
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"scannedAt": null,
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"scannerVersion": null,
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"flags": []
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}
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} |