Plugins

12 plugins

Run Agent Evaluation

Sets up evaluation framework, runs benchmarks, and produces comparative analysis of agent performance.

9 skills · plugin

Microsoft 365 Agents Toolkit

Toolkit for building and evaluating Microsoft 365 Copilot declarative agents — scaffolding, JSON manifest development, capability configuration, and eval workflows.

6 skills · plugin

ML Model Lifecycle

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

10 skills · plugin

Design Pricing Strategy

Design a pricing strategy by analyzing market, evaluating financial impact, and recommending pricing models.

6 skills · plugin

Monetization to Billing Pipeline

For product managers and finance ops: brainstorm strategies, evaluate financial impact, then execute billing workflows.

4 skills · plugin

Analyze and Prioritize Feature Requests

Install this pack to categorize, evaluate, and prioritize customer feature requests against product goals.

3 skills · plugin

Prototyping Testing

Prototyping and testing skills: wireframe specs, usability heuristics, heuristic evaluations, accessibility audits, A/B test design, and benchmark analysis.

8 skills · plugin

Google Cloud Well-Architected

For architects evaluating Google Cloud workloads against the Well-Architected Framework pillars: reliability, cost optimization, and operational excellence.

6 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

14 regulatory affairs & quality management skills for HealthTech/MedTech: ISO 13485 QMS, MDR 2017/745, FDA 510(k)/PMA, GDPR/DSGVO, ISO 27001 ISMS, CAPA management, risk management, clinical evaluation, SOC 2 compliance.

10 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

@alirezarezvani

Engineering Team

32 engineering skills: architecture, frontend, backend, fullstack, QA, DevOps, security, AI/ML, data engineering, Playwright (9 sub-skills), self-improving agent, Stripe integration, TDD guide, tech stack evaluator, Google Workspace CLI, a11y audit (WCAG 2.2), Azure cloud architect, GCP cloud architect, security pen testing, Snowflake development, adversarial-reviewer, ai-security, cloud-security,

16 skills · plugin

Results for “eval”

20 skills

Build and run evaluators for AI/LLM applications using Phoenix, covering error analysis, custom evaluators, experiments, and production monitoring.

36.2k · bundle

M365 Agent Evaluator

Create, run, and analyze evaluation suites for Microsoft 365 Copilot declarative agents using the @microsoft/m365-copilot-eval CLI.

Implement iterative evaluation and refinement loops for AI agent outputs, using self-critique, evaluator-optimizer patterns, and rubric-based scoring to improve quality.

orchestra-research

Langsmith Observability

Debug, evaluate, and monitor LLM applications with tracing, datasets, and built-in evaluators.

10.4k · bundle

Runs regression evaluations comparing agent edits against human-approved golden projects, and registers new goldens after human approval.

Arize Evaluator

Creates and runs LLM-as-judge evaluators on Arize, including managing tasks, column mappings, and continuous monitoring.

36.2k · bundle

More results

Prompt Engineer

Designs, optimizes, and evaluates prompts for LLMs, including structured outputs, chain-of-thought, and evaluation frameworks.

10.4k · bundle

Advanced Evaluation

Provides production-grade techniques for evaluating LLM outputs using LLMs as judges, covering direct scoring, pairwise comparison, bias mitigation, rubric generation, and confidence calibration.

16.9k · bundle

Create new skills, modify existing ones, and measure their performance through iterative evaluation and benchmarking.

Arize Prompt Optimization

Optimizes, improves, and debugs LLM prompts using production trace data, evaluations, and annotations from Arize AI.

36.2k · bundle

Provides expertise in Langfuse for LLM observability, including tracing, prompt management, evaluation, and integration with LangChain, LlamaIndex, and OpenAI.

Prompt Optimizer

Creates, optimizes, and iteratively refines agent prompts, system prompts, developer prompts, and reusable prompt templates with evals.

Prompt Engineer

Designs and optimizes prompts for LLM-powered applications, covering system prompt architecture, context management, output formatting, and evaluation.

nimoqup046-collab

Guides production AI systems: RAG pipelines, embeddings, vector databases, fine-tuning, prompt engineering, cost estimation, quality evals, and caching.

Guides production LLM operations: RAG pipelines, embeddings, vector databases, fine-tuning, prompt engineering, cost estimation, quality evals, and AI architectures.

Context Compression

Optimizes long-running agent sessions with structured context compression, summarization, and durable handoff summaries that preserve decisions, files, risks, and next actions.

16.9k · bundle

lucaspmarie-a11y

Provides guidance on production AI operations including RAG pipelines, vector databases, embeddings, fine-tuning, prompt engineering, cost estimation, and quality evaluation.

Implements production LLM operations: RAG pipelines, embeddings, vector databases, fine-tuning, advanced prompt engineering, cost estimation, quality evals, semantic caching, streaming, and agents.

Provides guidance and code for production AI workflows including RAG pipelines, vector databases, embedding indexing, prompt engineering, cost estimation, semantic caching, and quality evaluation.

dontbesilent2025

Dbs Good Question

Transforms fuzzy problems into structured briefs that AI agents can reason about, critique, and act upon, while evaluating how much of the problem can be automated.