ETL pipeline construction, data warehouse design, batch processing workflows, and data-driven feature development
Plugin data-engineering from marketplace claude-code-workflows in shotcowboystyle/ag-skills. Commands read from the repo's manifest — 11 days ago.
airflow-dag-patternsWrite, test or upgrade Apache Airflow 3 DAGs with the Task SDK (`airflow.sdk`), TaskFlow tasks, timetables and asset scheduling, dynamic task mapping, deferrable sensors, retries and failure callbacks. Use when the task is an Airflow DAG, an Airflow operator or sensor, or an Airflow 2 to 3 migration
data-quality-frameworksImplement data quality validation with Great Expectations 1.x, dbt data tests and model contracts, and ODCS data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.
dbt-transformation-patternsWrite and test dbt models in SQL, with sources and freshness, staging, intermediate and mart layers, incremental and microbatch models, data tests, unit tests and macros, in YAML that is valid for dbt Core 1.10+ and dbt v2. Use when the task is a dbt project or a SQL transformation that runs inside
spark-optimizationDiagnose and fix a slow or failing Apache Spark job (PySpark, Spark SQL, Spark 3.x and 4.x) from the Spark UI and query plan, covering shuffles, skew, join strategy, spills, small files, partition sizing and executor memory. Use when a Spark or Databricks job is slow, costly or dies with out-of-memo
/data-engineering:data-driven-featureBuild features guided by data insights, A/B testing, and continuous measurement
/data-engineering:data-pipelineDesign and implement batch and streaming data pipelines with ingestion, orchestration, dbt transformations, data quality checks, and monitoring
data-engineering-backend-architectDesign the backend for one feature or service, covering service boundaries, the API contract, data ownership, failure handling and the plan to build it. Use when a feature needs a backend design before implementation, or an existing API or service split needs review. Not for writing the implementati
data-engineerDesign, build or review one batch or streaming data pipeline, from source to tested output, using the data-engineering skills for Airflow, dbt, Spark and data quality. Use when the task is a specific pipeline, ELT job, warehouse model, event-tracking schema or pipeline validation, not a platform-wid
UX/UI design ops — briefs, tokens, components, screens and pages graded against live Awwwards and Mobbin references, plus Material 3/Compose, React Native, and web component design. Absorbs the former ui-design plugin.
47 skills · 39 commands · 4 agents
Image editing, batch operations, format conversion (WebP, AVIF, JPEG XL, PDF), metadata, and library organization — bucket by resolution, aspect ratio, orientation, format, capture time, and camera; dedupe near-duplicates.
28 skills · 19 commands
Drive an AI-generated video project end to end — brief, model selection, characters, script, storyboard, generation pipelines (text-to-image, image-to-video, voice, lip-sync), GPU-aware assembly, ComfyUI import/export, budgets, export — plus a curated index of agent-callable video and audio tooling.
13 skills · 11 commands · 7 agents · 3 MCP servers
Chain-of-custody evidence handling — hash, timestamp, inspect metadata, append to an immutable custody register, package as BagIt, verify, and sync to WORM or S3 Object Lock storage.
14 skills · 12 commands
Modern Python development with Python 3.12+, Django, FastAPI, async patterns, and production best practices
16 skills · 1 command · 3 agents
Work out the real baggage allowance for every segment of an itinerary, inventory what is carried by weight, solve the pack against the binding limit, price excess-baggage options, rank a leave-behind list, and render a counter card and packing list with Typst.
9 skills · 10 commands
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
This page updates itself from your repo. Add the badge to your README, or get it Featured to pin it above the organic results with a followed link to your site.