Generate abstract Control Flow Graph (CFG) representations of programs showing loops, branches, and function calls for static analysis or verification. Use when users need to: (1) Visualize program control flow structure, (2) Generate CFGs for static analysis tools, (3) Create control flow abstractions for formal verification, (4) Analyze program paths and reachability, (5) Document program structure. Supports both function-level (intraprocedural) and program-level (interprocedural) analysis with multiple output formats (textual, DOT/Graphviz, JSON).

Analyzes and optimizes code for better performance, memory usage, and efficiency. Use when code is slow, memory-intensive, or inefficient. Supports Python and Java optimization including execution speed improvements, memory reduction, database query optimization, and I/O efficiency. Provides before/after examples with detailed explanations of why optimizations work, complexity analysis, and measurable performance improvements.

Atheris is a coverage-guided Python fuzzer based on libFuzzer. Use for fuzzing pure Python code and Python C extensions.

Execute Juicebox production checklist. Trigger: "juicebox production", "deploy juicebox".

Implement Ideogram rate limiting, backoff, and request queuing patterns. Use when handling rate limit errors, implementing retry logic, or optimizing API request throughput for Ideogram. Trigger with phrases like "ideogram rate limit", "ideogram throttling", "ideogram 429", "ideogram retry", "ideogram backoff", "ideogram queue".

Migrate to Granola from Otter.ai, Fireflies, Fathom, tl;dv, or manual note-taking. Covers data export from source tools, parallel-run strategy, team transition, and historical data preservation. Trigger: "migrate to granola", "switch to granola", "granola from otter", "granola from fireflies", "replace meeting tool with granola".

Structure and data sources for the weekly inventory report. Load this when the task is "weekly report", "Monday report", or "summarize inventory status".

Setup synthetic monitoring for proactive performance tracking including uptime checks, transaction monitoring, and API health. Use when implementing availability monitoring or tracking critical user journeys. Trigger with phrases like "setup synthetic monitoring", "monitor uptime", or "configure health checks".

Four-phase debugging framework that ensures root cause investigation before attempting fixes. Never jump to solutions. Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

| Nuxt 4 core framework fundamentals: project setup, configuration, routing, SEO, error handling, and directory structure. Use when: creating new Nuxt 4 projects, configuring nuxt.config.ts, setting up routing and middleware, implementing SEO with useHead/useSeoMeta, handling errors with error.vue and NuxtErrorBoundary, or understanding Nuxt 4 directory structure.

Provides comprehensive GitHub operations using gh CLI and GitHub API. Activates when working with pull requests, issues, repositories, workflows, or GitHub API operations including creating/viewing/merging PRs, managing issues, querying API endpoints, and handling GitHub workflows in enterprise or public GitHub environments.

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

Add a "code mode" tool to an existing MCP server so LLMs can write small processing scripts that run against large API responses in a sandboxed runtime — only the script's compact output enters the LLM context window. Use this skill whenever someone wants to add code mode, context reduction, script execution, sandbox execution, or LLM-generated-code processing to an MCP server. Also trigger when users mention reducing token usage, shrinking API responses, running user-provided code safely, or adding a code execution tool to their MCP server — in any language (TypeScript, Python, Go, Rust, etc.).

Audit YouTube Ads campaign setup, video and Demand Gen inventory, Shorts, in-stream, CTV, creative, audiences, brand safety, bidding, and measurement. Use for YouTube Ads, video ads, pre-roll, bumper ads, skippable in-stream, Shorts ads, Demand Gen, VAC migration, CTV, or YouTube campaign optimization.

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

GitHub operations via `gh` CLI: issues, PRs, CI runs, code review, API queries. Use when: (1) checking PR status or CI, (2) creating/commenting on issues, (3) listing/filtering PRs or issues, (4) viewing run logs. NOT for: complex web UI interactions requiring manual browser flows (use browser tooling when available), bulk operations across many repos (script with gh api), or when gh auth is not configured.

GitHub operations via `gh` CLI: issues, PRs, CI runs, code review, API queries. Use when: (1) checking PR status or CI, (2) creating/commenting on issues, (3) listing/filtering PRs or issues, (4) viewing run logs. NOT for: complex web UI interactions requiring manual browser flows (use browser tooling when available), bulk operations across many repos (script with gh api), or when gh auth is not configured.