libconfig - Configuration management library. serviceConfig, extensionConfig, and scriptConfig load settings from files and environment variables. Configuration class provides advanced features like namespacing and storage backend loading. Use for service initialization, environment-specific settings, and runtime configuration.

Idiomatic context.Context usage in Golang — creation, propagation, cancellation, timeouts, deadlines, context values, and cross-service tracing. Apply when working with context.Context in any Go code.

Provides CI/CD pipeline configuration using GitHub Actions for Golang projects. Covers testing, linting, SAST, security scanning, code coverage, Dependabot, Renovate, GoReleaser, code review automation, and release pipelines. Use this whenever setting up CI for a Go project, configuring workflows, adding linters or security scanners, setting up Dependabot or Renovate, automating releases, or improving an existing CI pipeline. Also use when the user wants to add quality gates to their Go project.

Synthesizes all pipeline handoffs into a single human-readable project brief. Use when user says "generate docs", "create documentation", "document the project", or after validation passes. Do NOT use for deployment (use fabric-deploy) or architecture design (use fabric-design).

A decision-support framework that evaluates systems, architectures, and strategies through the entropy (decay) vs negentropy (growth) lens, while surfacing tacit knowledge gaps. Use this skill whenever the user is making architecture decisions, evaluating system designs, reviewing technical approaches, choosing between options, auditing existing systems, or planning strategies. Also trigger when the user explicitly asks to "apply the negentropy lens", mentions "entropy", "negentropy", "tacit knowledge", "knowledge engine", or "flip the switch". Nudge activation when you detect the user is at a decision point — even if they haven't asked for this lens — by briefly noting the entropic/negentropic dimension before proceeding.

Professional typography rules for UI design, web applications, software interfaces, and all screen-based text. Enforces timeless typographic correctness that LLMs consistently get wrong: proper quote marks, dashes, spacing, hierarchy, and layout. ENFORCEMENT MODE: When generating ANY HTML, CSS, React, JSX, or UI code containing visible text, auto-apply every rule in this skill silently — do not ask, do not explain, just produce correct typography. AUDIT MODE: When reviewing or improving existing interfaces or legacy code, flag violations and provide fixes. Trigger on: any HTML/CSS/React artifact creation, "build a landing page", "create a component", "design a UI", "fix the typography", "make this look professional", "review this layout", web design, presentation design, dashboard creation, document generation, or any task producing visible text for humans. Even if the user doesn't mention typography, apply these rules whenever generating UI output.

Frontend development guidelines for React/TypeScript applications. Modern patterns including Suspense, lazy loading, useSuspenseQuery, file organization with features directory, MUI v7 styling, TanStack Router, performance optimization, and TypeScript best practices. Use when creating components, pages, features, fetching data, styling, routing, or working with frontend code.

Root cause analysis and debugging protocols. Use when encountering errors, test failures, unexpected behavior, stack traces, or when code behaves differently than expected.

Use this skill to get documentation for third-party APIs, SDKs or libraries before writing code that uses them to ensure you have the latest, most accurate documentation. This is a better way to find documentation than doing web search. This includes when a user asks for tasks like "use the OpenAI API", "call the Stripe API", "use the Anthropic SDK", "query Pinecone", or any other time the user asks you to write code against an external service and you need current API reference. Fetch the docs with chub before answering, rather than relying on your pre-trained knowledge, which may be outdated because of recent changes to these APIs. Be sure to use this skill when the user asks for the latest docs, latest API behavior, or explicitly mentions chub or Context Hub. Ensure `chub` is available, run `chub --help`, then follow the instructions there.

Frames coding-agent work sessions with explicit intent capture and drift monitoring. Use when a session transitions from planning/Q&A to implementation for coding tasks, refactors, feature builds, bug fixes, or other multi-step execution where scope drift is a risk.

Frames coding-agent work sessions with explicit intent capture and drift monitoring. Use when a session transitions from planning/Q&A to implementation for coding tasks, refactors, feature builds, bug fixes, or other multi-step execution where scope drift is a risk.

Create, manipulate, and analyze geometries using geometry classes and geometry operators. Use for spatial calculations, geometry creation, buffering, intersections, unions, and mesh operations.

Work with ArcGIS Utility Networks for modeling and analyzing connected infrastructure including network tracing, associations visualization, and topology validation. Use for electric, gas, water, and telecom network analysis.

Work with ArcGIS Knowledge graphs for storing, querying, and visualizing connected data using KnowledgeGraphLayer, LinkChartView, and openCypher queries. Use for graph databases, relationship visualization, and entity exploration.

Create, manipulate, and analyze geometries using geometry classes and geometry operators. Use for spatial calculations, geometry creation, buffering, intersections, unions, and mesh operations.

Work with raster and imagery data including ImageryLayer, ImageryTileLayer, multidimensional data, pixel filtering, and raster analysis. Use for satellite imagery, elevation data, and scientific raster datasets.

Azure AI Content Understanding SDK for Python. Use for multimodal content extraction from documents, images, audio, and video.

Azure AI Content Safety SDK for Python. Use for detecting harmful content in text and images with multi-severity classification.

Build anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate/multivariate anomaly detection, time-series analysis, or AI-powered monitoring.