Optimize Docker images and containers for size, build speed, and runtime performance

Reviews Dockerfiles for best practices, security issues, and image size optimizations including multi-stage builds and layer caching. Use when working with Docker, containers, or deployment.

docker-reviewer

docker-rocker

VaultCPA Docker operations guide including common commands, troubleshooting, deployment procedures, and container management. Use when working with Docker, deploying services, or debugging container issues.

Secure Docker containers and images with hardening, scanning, and secrets management

Guidance for running and debugging tests in Docker environments for FastAPI + Vue/Tailwind projects.

Docker Compose orchestration for Vigil Guard v2.0.0 microservices (11 services). Use when deploying services, managing containers, troubleshooting Docker network issues, working with vigil-net, configuring docker-compose.yml, handling service dependencies, or working with 3-branch detection services (heuristics, semantic, prompt-guard).

Generate optimized Dockerfiles and docker-compose.yml with best practices and multi-stage builds

Learn Dockerfile fundamentals and best practices for building production-ready container images

Create and optimize Dockerfiles with BuildKit, multi-stage builds, advanced caching, and security. Use when: (1) Creating new Dockerfile, (2) Optimizing existing Dockerfile, (3) Reducing image size, (4) Improving security, (5) Using Python with uv, (6) Resolving cache or slow build issues, (7) Setting up CI/CD builds

Generate optimized, secure, production-ready Dockerfiles with multi-stage builds and best practices.

Generate optimized Dockerfiles with multi-stage builds and best practices. Use when containerizing applications or creating Docker configurations.

Build optimized, secure, and cache-efficient Docker images following production best practices.

Audit Dockerfiles for security, efficiency, and best practices.

Generate .dockerignore files to optimize Docker builds by excluding unnecessary files.

dockerization

Convert any document format to structured Markdown, JSON, or HTML using IBM Docling with AI-powered layout analysis.

Python document processing library for parsing PDF, DOCX, and 10+ formats with advanced layout understanding, unified document representation, and AI ecosystem integrations (LangChain, LlamaIndex, MCP server)

Document revision workflow tool (CLI: `rev`). Use when working with Word documents containing reviewer comments, importing track changes to markdown, replying to reviewer comments, building PDF/DOCX outputs, generating response letters, validating citations/DOIs, or any document revision task.

Write PRDs, specs, and project context optimized for coding assistants (Claude Code, Cursor, Copilot, Custom GPTs). Includes CLAUDE.md generation, session planning, and templates for creating documentation that tools can execute effectively.

Documentation usage analytics and insights. Integrate with Google Analytics, Algolia analytics, and custom tracking to measure documentation effectiveness, identify content gaps, and optimize user journeys.

Analyzes code changes and identifies documentation gaps. Scans git history, catalogs existing docs, and generates comprehensive analysis reports.

Generates comprehensive changelogs from Conventional Commits, maintains CHANGELOG.md files, and scaffolds project documentation like PRD.md or ADR.md. This skill should be used when creating changelogs, generating release notes, maintaining version history, documenting architectural decisions, or scaffolding project requirements documentation. Use for changelog generation, release notes, version documentation, ADR, PRD, or technical documentation.

Universal markdown content quality standards for active voice, heading hierarchy, accessibility compliance (alt text, WCAG AA contrast, screen reader support), and professional formatting. Essential for all markdown content creation across docs/, Hugo sites, plans/, and repository files. Auto-loads when creating or editing markdown content.

Diátaxis documentation framework for organizing content into four categories - tutorials (learning-oriented), how-to guides (problem-solving), reference (technical specifications), and explanation (conceptual understanding). Essential for creating and organizing documentation in docs/ directory.

Automatically update repository documentation whenever code changes (add/edit/refactor) occur. Use when modifying source code, public APIs/contracts, rendering/interaction/data/compute logic, diagnostics, or build/release/CI flows so docs stay consistent without asking.

Bootstraps documentation structure for projects. Creates initial README, architecture docs, and API documentation with project-aware templates.

Building, rendering library docs, and deploying docs.cloudposse.com. Use when working with the Docusaurus build process or regenerating auto-generated content.

Consolidate redundant documentation while preserving 100% of valuable content.

Technical writing patterns for README files, API documentation, architecture decision records (ADRs), changelogs, contributing guides, code comments, and docs-as-code workflows. Covers documentation structure, style guides, Markdown best practices, and documentation testing.

Validate consistency across SEED Design component documentation layers (design guidelines in ./docs/content/docs/components, Rootage specs in ./packages/rootage/components, and React docs in ./docs/content/react/components). Use when auditing documentation completeness, before releases, or validating new component docs.

Comprehensive guide for creating by-example tutorials - code-first learning path with 75-90 heavily annotated examples achieving 95% language coverage. Covers five-part example structure, annotation density standards (1-2.25 comments per code line PER EXAMPLE), self-containment rules, and multiple code blocks for comparisons. Essential for creating by-example tutorials for programming languages on educational platforms

Technical documentation discovery via context7 and web search. Capabilities: library/framework docs lookup, topic-specific search. Keywords: llms.txt, context7, documentation, library docs, API docs. Use when: searching library documentation, finding framework guides, looking up API references.

Guide users through structured co-authoring, improvement, and QA of documentation. Use when users want to write or improve docs such as proposals, technical specs, decision docs, READMEs, guides, API docs, or runbooks; or when they ask for doc review, doc QA, checklists, or templates to make documentation clearer, skimmable, and correct for readers.

Explores internal documentation (brain repos, Notion) for context

Fetch current documentation for libraries to ensure accurate, up-to-date code generation.

Generate Level 1 (README.md) user documentation from design docs. Use when creating or updating package README files for npm/GitHub.

Generate Level 2 (repository docs) from design docs. Use when

Generate Level 3 (documentation sites) from design docs. Use when

Generate documentation for code, APIs, and components

Generate hierarchical documentation structures optimized for AI coding agents with minimal token usage. Supports AGENTS.md, agent.d, and custom documentation formats.

General reference documents by domain. Use when creating architecture docs, strategy documents, specs, or guides.

docs-keeper

Orchestrates comprehensive documentation management by coordinating docs-analyzer, docs-bootstrapper, and mermaid-expert skills. Proactively monitors code changes and ensures documentation stays synchronized with the codebase.

Navigate hierarchical ai-docs indexes to find documentation. Check local docs FIRST for speed and curated context before web searching. Covers Claude Code, BAML, MCP, and other tracked libraries.

Activates the Technical Writer to generate, update, or refactor internal project documentation. Use when creating READMEs, ADRs, or technical guides.

Write YAML front matter for documentation pages with appropriate titles and descriptions for social cards.