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Comprehensive documentation specialist covering API documentation, technical

Code style and conventions audit with auto-fix capabilities for comprehensive style enforcement

This skill should be used when the user asks to "create a hookify rule", "write a hook rule", "configure hookify", "add a hookify rule", or needs guidance on hookify rule syntax and patterns.

Implement saga patterns for distributed transactions and cross-aggregate workflows. Use when coordinating multi-step business processes, handling compensating transactions, or managing long-running workflows.

Use when you have a written implementation plan to execute in a separate session with review checkpoints

Publish articles to X/Twitter

Integrate Replicate AI models with background processing, S3 storage, and credit systems

Opinionated backend development standards for Node.js + Express + TypeScript microservices. Covers layered architecture, BaseController pattern, dependency injection, Prisma repositories, Zod validation, unifiedConfig, Sentry error tracking, async safety, and testing discipline.

Use when you need to run a binary, trace execution, or observe runtime behavior. Runtime analysis via QEMU emulation, GDB debugging, and Frida hooking - syscall tracing (strace), breakpoints, memory inspection, function interception. Keywords - "run binary", "execute", "debug", "trace syscalls", "set breakpoint", "qemu", "gdb", "frida", "strace", "watch memory"

Azure AI Content Understanding SDK for Python. Use for multimodal content extraction from documents, images, audio, and video. Triggers: "azure-ai-contentunderstanding", "ContentUnderstandingClient", "multimodal analysis", "document extraction", "video analysis", "audio transcription".

Create and modify Argcfiles using the special syntax required. Use this when editing Argcfile.sh, @argc, or any shell script that contains `argc --argc-eval`.

Orchestrate a configurable, multi-member CLI planning council (Codex, Claude Code, Gemini, OpenCode, or custom) to produce independent implementation plans, anonymize and randomize them, then judge and merge into one final plan. Use when you need a robust, bias-resistant planning workflow, structured JSON outputs, retries, and failure handling across multiple CLI agents.