All Skills
8165 skills found
Skills List
pytorch-lightning
Deep learning framework (PyTorch Lightning / lightning package). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard, MLflow), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.
k-dense-aigenerate-image
Generate or edit images with AI models through the OpenRouter Image API (Gemini, Seedream, Recraft, GPT-Image, Riverflow). Use for photos, illustrations, artwork, concept art, visual assets, logos, and image editing or compositing from reference images. For flowcharts, circuits, pathways, and other technical diagrams, use the scientific-schematics skill instead.
k-dense-aipyzotero
Interact with Zotero reference management libraries using the pyzotero Python client. Retrieve, create, update, and delete items, collections, tags, and attachments via the Zotero Web API v3. Use this skill when working with Zotero libraries programmatically, managing bibliographic references, exporting citations, searching library contents, uploading PDF attachments, or building research automation workflows that integrate with Zotero.
k-dense-aiaeon
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
k-dense-ainetworkx
Create, analyze, and visualize complex networks and graphs in Python with NetworkX. Use when working with network/graph data structures, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks (random, scale-free, small-world), reading/writing graph file formats, or drawing network topologies. Common applications include social, biological, transportation, and citation networks.
k-dense-aitransformers
Hugging Face Transformers for loading Hub models, running pipeline inference, text generation, and Trainer fine-tuning on NLP, vision, audio, and multimodal tasks. Use when working with AutoModel, pipelines, tokenizers, or TrainingArguments—not for general ML outside the Transformers library.
k-dense-aisympy
Use when you need exact symbolic math in Python — algebra, calculus, equation solving, symbolic linear algebra, or code generation via lambdify/LaTeX. Prefer NumPy or SciPy when floating-point approximations are sufficient.
k-dense-aimarket-research-reports
Build evidence-traceable market research reports and assumption-driven market sizing or forecast scenarios. Use for market definition, industry and customer evidence, competitive landscapes, TAM/SAM/SOM reconciliation, forecast sensitivity, and auditable report scaffolds.
k-dense-aiinfographics
Create professional infographics using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3.6 Flash for quality review. Integrates research-lookup and web search for accurate data. Supports 10 infographic types, 8 industry styles, and colorblind-safe palettes.
k-dense-aishap
Explain and audit machine-learning predictions with SHAP. Use for selecting SHAP explainers and maskers, computing and validating feature attributions, handling multi-output explanations, and producing local or global SHAP visualizations.
k-dense-aiget-available-resources
Detect host inventory and effective CPU, memory, disk, scheduler, container, and accelerator limits when a user asks for resource-aware planning or before a clearly resource-sensitive local workload. Produces a redacted JSON snapshot and conservative planning helpers without stress tests or assuming visible host hardware is usable.
k-dense-aidask
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
k-dense-aimatlab
Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.
k-dense-aioptimize-for-gpu
GPU-accelerates scientific Python on NVIDIA hardware and verifies that the result is correct and faster. Use for CUDA/GPU optimization; CPU-bound NumPy, SciPy, pandas, scikit-learn, NetworkX, scikit-image, vector-search, image-processing, graph, simulation, or file-I/O workloads; CuPy, cuDF, cuML, cuGraph, cuVS, cuCIM, KvikIO, Warp, Newton, Numba-CUDA, or RAFT questions; and profiling, memory-transfer, kernel, or multi-GPU bottlenecks. Also use when large data-parallel Python code is slow and GPU acceleration is a plausible option, even if the user does not name CUDA.
k-dense-aiscikit-survival
Build, evaluate, and audit right-censored or competing-risk survival workflows with scikit-survival, including leakage-safe preprocessing, model selection, probability prediction, and censoring-aware metrics.
k-dense-aiopen-notebook
Self-hosted, open-source alternative to Google NotebookLM for AI-powered research and document analysis. Use when organizing research materials into notebooks, ingesting diverse content sources (PDFs, videos, audio, web pages, Office documents), generating AI-powered notes and summaries, creating multi-speaker podcasts from research, chatting with documents using context-aware AI, searching across materials with full-text and vector search, or running custom content transformations. Supports 16+ AI providers including OpenAI, Anthropic, Google, Ollama, Groq, and Mistral with complete data privacy through self-hosting.
k-dense-aiparallel-web
Use Parallel CLI for web search, URL extraction, deep research, structured data enrichment, entity discovery, and recurring web monitoring. Best for requests that explicitly need current web evidence, academic-source discovery, repeated entity lookups, exhaustive reports, or ongoing change tracking.
k-dense-ai
chakra-ui-migrate
Migrate Chakra UI projects from v2 to v3, covering package changes, codemods, provider setup, color mode, prop renaming, compound components, theming, recipes, and Next.js updates. Use this skill whenever a user is upgrading Chakra UI versions, encountering breaking changes after an upgrade, converting old v2 patterns (ColorModeScript, useColorModeValue, styleConfig, extendTheme, isDisabled, colorScheme, @chakra-ui/icons, framer-motion dependency), fixing compound component patterns, or asking about differences between Chakra UI v2 and v3 — even if they don't say "migrate" or "upgrade" explicitly.
chakra-uichakra-ui-refactor
Review, convert, and improve UI code using Chakra UI v3. Use this skill whenever a user wants to review Chakra UI code for issues, convert plain HTML/CSS, Tailwind, CSS Modules, or styled-components to Chakra UI, clean up messy Chakra components, fix layout structure or token usage, or asks anything like "is this correct", "what's wrong with this", "review my component", "refactor this", "clean up", "convert", or "chakra-ify this" — even without the words "review" or "refactor". Trigger on any request to check, improve, or convert Chakra UI code, however casually phrased.
chakra-uichakra-ui-builder
Build responsive, accessible UI components and layouts using Chakra UI v3, install or configure Chakra UI in new and existing projects, and design scalable themes using tokens, semantic tokens, recipes, and slot recipes. Use this skill whenever a user asks to build, create, or generate any UI component, page, form, dashboard, navbar, card, landing section, pricing table, or layout using Chakra UI; wants to add Chakra UI to a project, set up ChakraProvider, run CLI snippets, configure color mode, or fix provider wrapping; or asks about theming — defining brand colors, design tokens, semantic tokens, dark mode values, component recipes, slot recipes, typegen, or ejecting the default theme. Trigger on any Chakra UI building, setup, or theming or charts request, however casually phrased — "add my brand colors", "make a reusable card style", "build a bar chart", "show me a line chart", "make me a login form", "build a sidebar", "add Chakra to my app".
chakra-ui
marketing-council
When the user wants multiple expert perspectives on a marketing question — a simulated board of advisors staffed by legendary marketers (Seth Godin, David Ogilvy, Eugene Schwartz, April Dunford, Rory Sutherland, Alex Hormozi, Byron Sharp, and more). Also use when the user mentions 'marketing council,' 'board of advisors,' 'advisory board,' 'what would Seth Godin say,' 'what would Ogilvy think,' 'channel Hormozi,' 'get multiple perspectives,' 'debate this,' 'have the council review,' 'marketing mentors,' or asks how a famous marketer would approach their problem. The council gives each advisor's take through their documented frameworks, surfaces where they disagree, and synthesizes a recommendation. For executing the winning direction, hand off to positioning, offers, copywriting, ads, or the relevant skill.
coreyhaines31
game-setup-and-config
Use this skill when creating a new Phaser 4 game instance or configuring GameConfig options. Covers renderer selection, canvas setup, scaling, pixel art, FPS settings, boot sequence, and all config sub-objects. Triggers on: new Phaser.Game, GameConfig, game setup, renderer, pixel art, FPS.
phaserjsmarketing-loops
When the user wants to set up a recurring, self-running marketing workflow — a repeatable loop an AI agent runs on a cadence (weekly, daily, on a trigger) rather than a one-off task. Also use when the user mentions 'marketing loop,' 'recurring marketing workflow,' 'automate my marketing,' 'marketing on autopilot,' 'weekly marketing review,' 'ad fatigue check,' 'content refresh loop,' 'churn watch,' 'ranking drop alert,' 'always-on marketing,' 'marketing automation workflow,' or 'run this every week.' Use this to pick, adapt, and schedule an ongoing marketing loop that orchestrates the other marketing skills. For one-off marketing ideas, see marketing-ideas. For the experimentation loop specifically, see ab-testing.
coreyhaines31
salesforce-flow-design
Salesforce Flow architecture decisions, flow type selection, bulk safety validation, and fault handling standards. Use this skill when designing or reviewing Record-Triggered, Screen, Autolaunched, Scheduled, or Platform Event flows to ensure correct type selection, no DML/Get Records in loops, proper fault connectors on all data-changing elements, and appropriate automation density checks before deployment.
github