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Found 1,267 Skills
Browser automation skill for controlling Google's NotebookLM. Handles reading and querying notebooks, adding sources (URLs, text, files, YouTube links, synthesized content), generating Studio outputs (Audio Overview, infographics, slide decks, study guides, briefing docs, mind maps, timelines, FAQs), and creating new notebooks. Triggers on any phrase involving NotebookLM — 'open NotebookLM', 'check my [name] notebook', 'pull info from NotebookLM', 'ask my notebook about X', 'add [source] to NotebookLM', 'create an infographic in NotebookLM', 'use NotebookLM Studio', 'generate a slide deck from my notebook', or any variation where the goal involves NotebookLM. Requires browser automation environment — fails gracefully when unavailable.
Guides organizational and business storytelling—narrative structure (setup, tension, resolution), audience-tailored stories for executives, customers, boards, and teams, honest data and metrics framing, product and strategy narratives, incident and postmortem storytelling, and actuarial or insurance risk narratives for non-technical audiences. Covers story spine, key messages, and visual or slide narrative outlines. Use when the user says "tell the story", "storytelling", "narrative for executives", "data story", "board presentation narrative", "explain with a story", "story arc", "key message", "compelling narrative", "pitch story", or "incident story"—not cross-department reframing only (cross-department-translation), company-wide comms cadence and crisis wording packs (communication-lead), long-form creative fiction or screenwriting, brand copy without strategy context, or technical documentation and API reference (tech-writer-researcher).
Builds Moran's I spatial autocorrelation workflows in CARTO. Triggers when the user mentions spatial autocorrelation, Moran's I, spatial dependency, spatial correlation, spatial outliers, HH HL LH LL quadrants, high-high clusters, low-low clusters, spatial weight matrix, "is there clustering", "are values spatially correlated", local indicators of spatial association, LISA, spatial randomness test, or wants to determine whether a variable exhibits spatial clustering, dispersion, or randomness across a gridded dataset. Also relevant when the user needs to classify locations into cluster types (HH, HL, LH, LL) rather than just identifying hotspots and coldspots.
Real-time stereo depth estimation using FastFoundationStereo (FFS), the distilled bp2 commercial variant of FoundationStereo. Predicts disparity maps from stereo image pairs with ~10× lower latency than full FoundationStereo. Use when training, evaluating, exporting, or running inference for a TAO FastFoundationStereo (FFS) model. Trigger phrases include "train fast stereo", "real-time stereo disparity", "FastFoundationStereo", "distilled stereo depth".
Check current Railway project status for this directory. Use when user asks "railway status", "is it running", "what's deployed", "deployment status", or about uptime. NOT for variables or configuration queries - use railway-environment skill for those.
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.
Tailwind CSS 4 patterns and best practices. Trigger: When styling with Tailwind (className, variants, cn()), especially when dynamic styling or CSS variables are involved (no var() in className).
Shell scripting best practices for writing safe, portable, and maintainable bash/sh scripts (formerly shell-scripts). Use when writing, reviewing, or refactoring shell scripts. Triggers on shell scripts, bash, sh, POSIX, ShellCheck, error handling, quoting, variables.
Use when working with ANY GPU rendering, Metal, OpenGL migration, shaders, 3D content, RealityKit, AR, or display performance. Covers Metal migration, shader conversion, RealityKit ECS, RealityView, variable refresh rate, ProMotion.
Dead code & legacy audit worker (L3). Checks unreachable code, unused imports/variables/functions, commented-out code, backward compatibility shims, deprecated patterns. Returns findings.
Creates Ansible roles with proper structure, tasks, handlers, and variables. Use when creating Ansible roles, organizing automation tasks, or structuring configuration management.
Analyze drug safety signals from FDA adverse event reports, label warnings, and pharmacogenomic data. Calculates disproportionality measures (PRR, ROR), identifies serious adverse events, assesses pharmacogenomic risk variants. Use when asked about drug safety, adverse events, post-market surveillance, or risk-benefit assessment.