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”

108 skills

Evaluates machine learning classifiers on their ability to distinguish signal from background in particle physics simulations, measuring how well algorithms rank signal events above background ones using the AUC metric.

Evaluates speaker verification models by computing true positive rate at fixed false positive rate thresholds, probing embedding space separation of same-speaker versus different-speaker pairs.

Benchmarks large language models on symbolic music understanding and instruction following using text-based ABC notation, covering syntax parsing, error detection, segment-level reasoning, and sequence-level musical analysis.

Evaluates the faithfulness of abstractive summaries by generating questions from summary sentences and verifying if the answers can be extracted from the source document, reporting Pearson and Spearman correlations with human judgments.

Benchmarks systems on the Abstraction and Reasoning Corpus (ARC) by requiring inference of abstract transformation rules from few input-output grid demonstrations and application to novel test cases, reporting the fraction of tasks solved.

Tao Train Deformable Detr

Train, evaluate, export, quantize, and run inference for a Deformable DETR 2D object detection model using TAO, with deformable attention for efficient multi-scale feature processing.

Benchmarks zero-shot in-context learning on BIG-Bench Hard multiple-choice tasks, comparing self-generated demonstrations against direct prompting and chain-of-thought baselines, and reports accuracy.

Evaluates image captions by converting them into scene graphs and computing an F-score over semantic propositions, measuring how well a generated caption captures the meaning of an image compared to human references.

Benchmarks energy-function-based safe control algorithms on the BIS (Benchmark of Interactive Safety) dataset, scoring safety, efficiency, and hybrid performance in human-robot and robot co-working scenarios.

Evaluates text-to-image generation models by decomposing assessment into five specialized skills (object presence, count, spatial relations, scale, and text rendering) and open-ended prompts, producing interpretable binary scores with visual and textual explanations.

编写评估FastText文本分类模型的Python函数，计算accuracy、F1、recall和precision指标，并处理特定格式的标签文本分割。

Evaluates automated metrics and vision-language models on identifying granular errors in detailed image descriptions and ranking paired descriptions against human judgments, using macro F1, pairwise accuracy, Spearman rank ρ, and Kendall's τ.

Nemo Automodel Recipe Development

Create and modify NeMo AutoModel training and evaluation recipes, including YAML structure, builders, and execution flow.

Tao Train Segformer

Trains, evaluates, exports, quantizes, and runs inference for SegFormer semantic segmentation models using NVIDIA TAO.

085 Aeon 556c1766

Provides guidance on using the Aeon library for time series forecasting, covering model selection, implementation, and evaluation.

Measures distributional similarity between original GAN-generated images and their semantically manipulated counterparts using the Fréchet Inception Distance (FID) metric.

Scores generated text for morphosyntactic well-formedness by measuring how closely it adheres to language-specific dependency rules extracted from treebanks.

Computes CIDEr and related metrics to score how well generated image descriptions align with human consensus, using reference sentences and triplet annotations.

Trains, evaluates, exports, and runs inference for person re-identification models using TAO, learning discriminative embeddings for cross-camera matching.

Tao Train Single Step

Fine-tune a TAO model with standard supervised training, evaluation, and export, with AutoML bypass and platform-specific credential intake.

Tao Train Pose Classification

Train, evaluate, export, and run inference for pose classification models using ST-GCN on skeleton keypoint sequences.

Fine Tuning Expert

Fine-tune LLMs using LoRA, QLoRA, and PEFT with Hugging Face, including dataset preparation, hyperparameter tuning, evaluation, and deployment.

10.4k · bundle

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

Turns model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.

Tao Train Centerpose

Train, evaluate, export, and run inference for CenterPose models used in 6-DoF object pose estimation with keypoint regression.

Tao Train Pointpillars

Train, evaluate, export, prune, and run inference for PointPillars 3D object detection models from LiDAR point clouds using NVIDIA TAO.

Designs and implements RAG pipelines, covering document chunking, embedding strategies, hybrid search, answer synthesis with source attribution, and evaluation using RAGAS metrics.

Tao Train Mask2former

Train, evaluate, export, quantize, and run inference on Mask2Former models for panoptic, instance, and semantic segmentation using NVIDIA TAO.

Tao Train Foundation Stereo

Trains, evaluates, exports, and runs inference on FoundationStereo models for stereo depth estimation and 3D reconstruction from stereo image pairs.

Turn model work into a production ML system with data contracts, repeatable training, measurable quality gates, deployable artifacts, and operational monitoring.

leandrobenjaminl

Time Series Analysis

Analiza series temporales: tendencia, estacionalidad y pronóstico con Prophet, statsmodels y ML, incluyendo descomposición, tests de estacionariedad y evaluación contra baselines.

sakamoto-family-smile

Turn model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.

Tao Train Image Classification

Train, evaluate, distill, quantize, export, and run inference for PyTorch-based TAO image classification models with support for multiple backbones.

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

Benchmarks a text-to-text transformer across GLUE, SuperGLUE, CNN/Daily Mail, SQuAD, and WMT, reporting GLUE average, BLEU, ROUGE-2-F, and Exact Match scores.

Benchmarks medical AI agents on synthetic EHR tasks, measuring success rates for data retrieval, temporal aggregation, and threshold-based conditional logic with exact-match scoring.