Help us improve
Share bugs, ideas, or general feedback.
Share bugs, ideas, or general feedback.
Share bugs, ideas, or general feedback.
By rohitg00
Track ML experiments by logging parameters, metrics, artifacts, metadata, and environment details. Compare runs side-by-side from a tracking store, analyze parameter sensitivity, generate visualizations, identify best configurations, and receive recommendations for next experiments.
npx claudepluginhub rohitg00/awesome-claude-code-toolkit --plugin experiment-trackerShare bugs, ideas, or general feedback.
Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Set up ML experiment tracking
Evaluate and compare ML model performance metrics
Skills for tracing, evaluating, and improving AI agents with MLflow. Supports the full agent improvement loop: instrument → trace → evaluate → iterate → validate.
ML engineering plugin: Give your AI coding agent ML engineering superpowers.
ML/perf investigation skills: topic, plan, judge, run, sweep
Autonomous experiment loop — iteratively optimize any metric with git-tracked experiments
Persistent memory for AI coding agents -- captures tool usage, compresses via LLM, injects context into future sessions. 12 hooks, 41 MCP tools, 4 skills, real-time viewer.
Complete AI coding workflow system. Self-correcting memory + persistent FTS5-indexed research wikis + auto-research loop + multi-LLM council on a single SQLite store. 33 skills, 8 agents, 22 commands, 37 hook scripts across 24 events. Cross-agent via SkillKit.
Complete developer toolkit for Claude Code
Find and remove dead code across the codebase
Generate comprehensive unit tests for any function or module
Own this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge.
Sign in to claimOwn this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge.
Sign in to claim