Plugins

3 plugins

ML Model Lifecycle

Train, evaluate, and deploy a production ML system with monitoring.

10 skills · plugin

Visual Critique

Visual critique skills: hierarchy analysis, brand consistency checks against mood/voice/tokens, composition evaluation, and typography audits — with a /critique-screen command that compiles a prioritised fix list.

7 skills · plugin

@alirezarezvani

Multi-agent collaboration — spawn N parallel subagents that compete on code optimization, content drafts, research approaches, or any task that benefits from diverse solutions. 7 slash commands (/hub:init, /hub:spawn, /hub:status, /hub:eval, /hub:merge, /hub:board, /hub:run), agent templates, DAG-based orchestration, LLM judge mode, message board coordination.

8 skills · plugin

Results for “l-eval”

6 skills

Eval Driven Dev

Build automated evaluation pipelines for Python LLM applications using real LLM calls and structured test datasets.

36.2k · bundle

More results

Execute the full AgentHub competition lifecycle in a single command: initialize, capture baseline, spawn agents, evaluate results, and merge the winner.

Provides a formal evaluation framework for Claude Code sessions, implementing eval-driven development (EDD) principles to define pass/fail criteria, measure reliability with pass@k metrics, and create regression test suites.

Formal evaluation framework for Claude Code sessions implementing eval-driven development (EDD) principles.

sakamoto-family-smile

Formal evaluation framework for Claude Code sessions implementing eval-driven development (EDD) principles.

Gan Style Harness

Uses a multi-agent generator-evaluator feedback loop to build high-quality applications from a single prompt, inspired by GANs and Anthropic's harness design.