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Found 1,443 Skills
Generate videos using TensorsLab's AI video generation models. Supports text-to-video and image-to-video generation with automatic prompt enhancement, progress tracking, and local file saving. Use for generating videos from text descriptions, animating static images, creating cinematic content, and various aspect ratios. Requires TENSORSLAB_API_KEY environment variable. Video generation takes several minutes.
Interact with the Overvy kanban board via curl. Use when the user wants to list issues, list AI tickets, work on a ticket, move issues between lanes, or check board status. Triggers include "overvy", "list AI tickets", "show me ready tickets", "what tickets are available", "what should I work on", "work on ticket", "work on any ticket", "pick a ticket", "start a ticket", "pick up an issue", "my issues", "kanban board", "move issue", "list issues", "board status", or references to lanes like "ready", "in progress", "in review", "done". Requires OVERVY_API_KEY environment variable.
Expert knowledge for Azure AI Anomaly Detector development including troubleshooting, best practices, architecture & design patterns, limits & quotas, configuration, and deployment. Use when using univariate/multivariate APIs, Docker/IoT Edge containers, predictive maintenance flows, or regional limits, and other Azure AI Anomaly Detector related development tasks. Not for Azure AI Metrics Advisor (use azure-metrics-advisor), Azure Monitor (use azure-monitor), Azure Machine Learning (use azure-machine-learning).
Run Karpathy-style autoresearch optimization on any content. Generates 50+ variants, scores with a 5-expert simulated panel, evolves winners through multiple rounds, outputs optimized version + full experiment log. Use when optimizing landing pages, email sequences, ad copy, headlines, form pages, CTA text, or any conversion-focused content. Triggers on "optimize this page", "run autoresearch", "score these variants", "A/B test this copy".
Apply Partial Least Squares SEM (PLS-SEM) with reflective and formative measurement models to maximize explained variance in endogenous constructs. Use this skill when the user has small samples, formative indicators, or exploratory models, needs to assess AVE/CR/HTMT, or when they ask 'should I use PLS or CB-SEM', 'how do I handle formative constructs', or 'what is the path coefficient significance'.
Use when refactoring code with poor names, when asked to improve naming, or when a user struggles to name a class/method/variable. Symptoms include -Manager/-Util suffixes, single-letter variables, process/handle/do verbs, primitive obsession, god methods with multiple responsibilities.
Plan-then-execute implementation against SPEC.md. Native single-thread loop, no sub-agents. On test or build failure, auto-invokes the backprop skill before retrying — a failed verification always considers whether a new §V invariant would prevent recurrence. Triggers when the user asks to build, implement, execute the spec, or tackle a specific §T task (`build §T.3`, `build --next`, `implement next task`, `run the build`). Expects SPEC.md to exist; if not, defers to the spec skill.
Elite frontend image-direction skill for generating premium, artistic, implementation-friendly website design references. Uses combinatorial variation to avoid repetitive AI aesthetics, enforces cinematic hero minimalism, strong hierarchy, generous spacing, image-led composition, and anti-slop visual discipline. For visual frontend tasks, this skill must first generate the design image(s) itself, deeply analyze them, then implement the frontend to match them as closely as possible.
Rare disease genomics research -- disease identification via Orphanet, causative gene discovery, gene-disease validity assessment via GenCC, pathogenic variant lookup via ClinVar, HPO phenotype mapping, epidemiology and prevalence data, clinical trial search, and literature review. Use when users ask about rare diseases, orphan diseases, genetic causes of rare conditions, Orphanet codes, HPO phenotypes, gene-disease validity, rare disease prevalence, or treatment options for rare genetic disorders.
Solve Linear Programming (LP), Mixed-Integer Linear Programming (MILP), and Quadratic Programming (QP, beta) with the Python API. Use when the user asks about optimization with linear or quadratic objectives, linear constraints, integer variables, scheduling, resource allocation, facility location, production planning, portfolio optimization, or least squares.
Load a sharded, on-disk dataset (sharded .npy, Parquet/Arrow, raw binary, sharded HDF5, custom layouts) into a distributed cuPyNumeric ndarray via a manual partition + leaf @task launch with CPU/OMP/GPU variants. Use when no single-call loader fits, including when per-shard row counts differ across files. Prefer cupynumeric.load or legate.io.hdf5.from_file when they apply.
Generate and edit AI images with NanoBanana (Gemini-based) via AceDataCloud API. Use when creating images from text prompts or editing existing images with text instructions. Supports nano-banana, nano-banana-2, nano-banana-pro and their :official variants.