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Found 1,668 Skills
Full-stack AI content pipeline for automated research, script generation, Facebook posting, and video rendering using Claude/OpenAI and Remotion
Automate content creation from research to video generation using AI-powered content pipeline with Claude, OpenAI, and Remotion
End-to-end ETL pipeline for Harvard Art Museums API with SQL analytics and Streamlit visualization
Build end-to-end ETL pipelines with Harvard Art Museums API, SQL analytics, and Streamlit visualization
End-to-end retail ETL pipeline using PySpark, SQL Server, and Medallion Architecture (Bronze/Silver/Gold layers) for data warehousing
Operate the Teams meeting summary pipeline via Hermes CLI — summarize meetings, inspect pipeline status, replay jobs, manage Microsoft Graph subscriptions.
Use when the user asks to "improve a metric", "run labs", "leave feedback on a metric", "add to labs", "fix metric accuracy", "review metric results", "find misaligned metrics", or "iterate on metric quality". Covers the metric improvement cycle, the feedback workflow, and the labs pipeline used to refine metric accuracy over time.
Build clinical/healthcare deep-learning pipelines with PyHealth — loading EHR/signal/imaging datasets (MIMIC-III/IV, eICU, OMOP, SleepEDF, ChestXray14, EHRShot), defining tasks (mortality, readmission, length-of-stay, drug recommendation, sleep staging, ICD coding, EEG events), instantiating models (Transformer, RETAIN, GAMENet, SafeDrug, MICRON, StageNet, AdaCare, CNN/RNN/MLP), training with the PyHealth Trainer, computing clinical metrics, and using medical code utilities (ICD/ATC/NDC/RxNorm lookup and cross-mapping). Use this skill whenever the user mentions PyHealth, MIMIC, eICU, OMOP, EHR modeling, clinical prediction, drug recommendation, sleep staging, medical code mapping, ICD/ATC codes, or any healthcare ML pipeline that fits the dataset → task → model → trainer → metrics pattern, even if "PyHealth" isn't named explicitly.
All-in-one content director that bundles FOUR format specialists — talking-to-camera, silent POV, dance, and stitch/duet — behind a single front door. Ingests the user's Instagram or TikTok handle, then in Stage 0 asks which KIND of trend they want to make (talking / POV / dance / duet, each explained), recommends a format from their profile when they're unsure, and can present a cross-format sampler menu (~10 real trend cards with links spanning all four formats) so the user picks one card. Once a format (and optionally a specific trend) is locked, it loads the matching format playbook from `formats/<format>.md` and runs that pipeline end-to-end. Triggers — "be my content director" (when the user wants to choose a format), "what kind of trend should I make", "talking vs pov vs dance vs duet", "show me trends across formats", "content director bundle", "content-director".
Manage repositories, check pipelines, review merge requests, and monitor CI/CD on GitLab
ElevenLabs TTS integration for video narration. Use when generating voiceover audio, selecting voices, or building script-to-audio pipelines
Implement data quality checks, validation rules, and monitoring. Use when ensuring data quality, validating data pipelines, or implementing data governance.