Plugins

4 plugins

Run Agent Evaluation

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

9 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

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

Results for “evaluation”

8 skills

eval-performance

Diagnose and improve MSBuild project evaluation performance by analyzing phases, glob patterns, import chains, and property functions.

Improve CLI build performance by enabling MSBuild Server for persistent caching of evaluation results across sequential builds.

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

More results

Spawns multiple parallel AI agents that compete on the same task using isolated git worktrees, evaluates results, and merges the best solution.

20.4k · bundle

edge-strategy-reviewer

Reviews trading strategy drafts for edge plausibility, overfitting risk, sample size adequacy, and execution realism, outputting PASS/REVISE/REJECT verdicts with confidence scores.

Runs a five-phase pipeline—evaluation, specification, implementation, review, and QA—to build a feature end-to-end with specialized agents.

microsoft-foundry

Deploy, evaluate, fine-tune, and manage Microsoft Foundry agents end-to-end using Azure Developer CLI and MCP tools.

tao-run-deft-aoi

Automates the full DEFT AOI improvement loop for NVIDIA TAO VisualChangeNet / ChangeNet PCB inspection models, including baseline evaluation, RCA, synthetic defect generation, data mining, retraining, and deployment gating until KPI targets are met.