CLI-powered model exploration: relationships, DAX, Power Query, focused browser views and offline snapshots.
Plugin semantic-model-viewer from marketplace semantic-model-tools in MrPerfectH/Semantic-Model-Viewer. Commands read from the repo's manifest — today.
explainExplains a Power BI model or measure through the Semantic Model Viewer CLI using focused browser views and annotated walkthroughs. Use when asked for a visual model explanation.
openOpens related tables and dependent measures together through the Semantic Model Viewer CLI. Use for focused Power BI model exploration.
setupInstalls a stable smv CLI command on the user's PATH that follows Semantic Model Viewer plugin upgrades.
smv-explainIllustrate semantic-model explanations with the Semantic Model Viewer CLI using annotated model views, external results, and proposed changes. Use when a user wants to understand model logic, discuss a suspected issue, or see a modeling idea.
snapshotExports a Power BI model as standalone interactive HTML using the Semantic Model Viewer CLI. Use when asked to save or share an offline model view.
stopLists and stops Semantic Model Viewer managed sessions, including multi-view workspaces.
Agentic QE (external: maintained in proffesor-for-testing/agentic-qe, pinned to v3.15.17): a quality-engineering fleet with 11 QE agents, 9 skills, 9 commands, the agentic-qe MCP server pinned to the plugin version, and the aqe-mod guard that refuses destructive operations on AQE learning data
9 skills · 9 commands · 11 agents · 1 MCP server
Automates browser interactions for web testing, form filling, screenshots, and data extraction
12 skills
Install the "AAS Data Analytics & Business Intelligence" workflow plugin from Agentic Awesome Skills.
16 skills
Databricks skills for the CLI, Apps, Lakebase, Model Serving, Lakeflow Jobs, Spark Declarative Pipelines, Declarative Automation Bundles (DABs), and classic-to-serverless migration.
37 skills · 2 commands · hooks
The official CCXT MCP server plus the ccxt-mcp usage skill — market data, balances and opt-in trading across 100+ crypto exchanges and prediction markets, with keys kept local.
1 MCP server
Eval-gated LLM fine-tuning lifecycle (LoRA/QLoRA, DPO, GRPO/RLVR, vision SFT, quantized export). Use when fine-tuning an open-weights model end-to-end: building the eval harness first, selecting method and model, preparing data, training with Unsloth or TRL, gating checkpoints, and exporting GGUF/FP8.
10 skills · 2 commands · 3 agents
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