productivity▌

Interact with Atlassian Jira from the command line using jira-cli.

Time-boxed technical spike documents for researching critical development decisions before implementation. \n \n Generates structured markdown spike files with clear objectives, research questions, investigation plans, and decision frameworks \n Supports six spike categories: API Integration, Architecture & Design, Performance & Scalability, Platform & Infrastructure, Security & Compliance, and User Experience \n Includes built-in checklists for research tasks, success criter

Guides masonry layout design for content with varying heights. Masonry stacks items in columns without distinct rows; items fill gaps like a brick wall. Best for image galleries, portfolios, and discovery-focused platforms.

Multi-provider AI image generation with text-to-image, reference images, batch processing, and quality presets. \n \n Supports seven providers: OpenAI, Google, OpenRouter, DashScope, Jimeng, Seedream, and Replicate with automatic provider selection or explicit override \n Handles single images via CLI flags or batch parallel generation from JSON files with configurable worker counts and per-provider throttling \n Supports reference images (Google, OpenAI, OpenRouter, Replicate, Seedream), custom

This skill enables Claude to analyze content analytics data, generate comprehensive reports, identify performance trends, calculate ROI and revenue attribution, and provide actionable insights for content optimization.

[Begins Step 1 with warm, inviting questions] \n \n ### Example 2: Quick Command Setup\n \n User: \"/novel-architect an english novel named lost-horizon 'A man discovers his small town is slowly disappearing from maps'\"

Systematic discovery of novel small molecule binders using 60+ ToolUniverse tools across druggability assessment, known ligand mining, similarity expansion, ADMET filtering, and synthesis feasibility.

../../../engineering-team/senior-computer-vision/SKILL.md

Create app store screenshots and preview videos via inference.sh CLI.

Coverage-guided fuzzer built into LLVM for finding bugs in C/C++ code with minimal setup. \n \n In-process fuzzer that instruments code at compile time to track coverage; automatically minimizes crashing inputs and maintains a corpus of interesting test cases \n Supports AddressSanitizer, UndefinedBehaviorSanitizer, and MemorySanitizer for detecting memory errors, undefined behavior, and uninitialized reads \n Harnesses written for libFuzzer are compatible with AFL++, enabling easy migration to