Expert guide for executing the Google Gemini CLI in non-interactive and headless modes. Covers command syntax, piping input, output handling, and automation patterns. Use when running gemini commands, piping context to Gemini, scripting Gemini workflows, or using interactive shell mode. Delegates to gemini-cli-docs for official command references.

Run Gemini CLI commands from Claude with correct Node version. Use when user asks to run Gemini CLI, test Gemini traces, or debug Gemini telemetry.

Expert guide for creating custom Gemini CLI commands. Covers slash command definitions (.toml), argument parsing, and shell execution. Use when creating custom Gemini commands, defining TOML command files, adding command arguments, or building extension-based commands. Delegates to gemini-cli-docs.

Expert guide for configuring Google Gemini CLI. Covers global vs project settings.json, Trusted Folders, Policy Engine, and environment variables. Use when configuring Gemini settings, managing trusted folders, setting up security policies, or troubleshooting configuration precedence. Delegates to gemini-cli-docs for official references.

Facilitates context sharing and strategic delegation between Claude Code and Gemini CLI. Syncs CLAUDE.md to GEMINI.md and provides agent selection guidance. Use when onboarding Gemini to a project, syncing instructions between agents, or deciding whether to use Claude or Gemini for a specific task.

Strategic patterns for Claude-to-Gemini delegation. Covers decision criteria, execution patterns, result parsing, and error handling. Use when determining if a task should be delegated to Gemini CLI.

Gemini CLI delegation workflow implementing delegation-core for Google's Gemini models.

Strategic patterns for codebase exploration using Gemini's large context window. Covers token thresholds, model routing, and exploration strategies. Use when deciding between Claude and Gemini for exploration, analyzing large codebases, or choosing between Flash and Pro models for context size.

A specialized skill for frontend development tasks using the Gemini CLI. It leverages Gemini's multimodal capabilities for generating UI code (React, Tailwind CSS) from descriptions or images (screenshots).

Create distinctive, production-grade frontend interfaces using Gemini 3 Pro for design ideation. Use this skill when you want Gemini's creative perspective on web components, pages, or applications. Generates bold, polished code that avoids generic AI aesthetics.

Patterns for prompting Gemini to generate conceptual images for game development. Use when creating concept art, UI mockups, character designs, environment sketches, or visual references.

Parse Gemini CLI headless output (JSON and stream-JSON formats). Covers response extraction, stats interpretation, error handling, and tool call analysis. Use when processing Gemini CLI programmatic output.

Expert guide for Model Context Protocol (MCP) integration with Gemini CLI. Covers MCP server configuration (HTTP, SSE, Stdio), connection management, and tool permissions. Use when adding MCP servers to Gemini, configuring transports, troubleshooting MCP connections, or managing tool permissions. Delegates to gemini-cli-docs.

Central authority for Gemini CLI sandboxing and isolation. Covers Docker, Podman, macOS Seatbelt profiles, and security boundaries. Use when enabling sandboxing, choosing sandbox methods, configuring Seatbelt profiles, or troubleshooting sandbox issues. Delegates 100% to gemini-cli-docs for official documentation.

Central authority for Gemini CLI session management. Covers session resume, retention policies, session browser, and cleanup. Use when resuming Gemini sessions, configuring retention, browsing past sessions, or managing session storage. Delegates 100% to gemini-cli-docs for official documentation.

Optimize token usage when delegating to Gemini CLI. Covers token caching, batch queries, model selection (Flash vs Pro), and cost tracking. Use when planning bulk Gemini operations.

Gemma Domain Trainer (Prototype)

Generate concise commit messages based on conversation context and minimal git inspection.

Generate fast-check property tests following project conventions

Expert in OCI Generative AI Dedicated AI Clusters - deployment, fine-tuning, optimization, and production operations

Generate images using Google GenAI Nano Banana Pro model via CLI. Use when the user asks to create images, generate pictures, make AI art, do image-to-image transformations, place people in scenes, or create character variations.

Convert between gene identifier systems including Ensembl, Entrez, HGNC symbols, and UniProt. Use when mapping IDs for pathway analysis or matching different data sources.

---name: gene-panel-design-agent

**Purpose:** Critical analysis and improvement of agent skills

Cross-domain evaluation to estimate generality and detect blind spots. Use when asked to assess broad capability, compare models across domains, or identify missing skills.

Generate two distinct, creative, and copyright-compliant ad copy variations based on campaign parameters and research insights. Use when creating advertising text content including headlines, body copy, and calls-to-action. Triggers on requests to write ad copy, create ad text, generate headlines, or develop platform-specific ad messaging for A/B testing.

Generate two distinct, AI-powered image variations for advertising campaigns using Google Gemini's image generation capabilities. Use when creating visual assets for ads based on campaign parameters and research insights. Triggers on requests to generate ad images, create visual assets, produce image variations for A/B testing, or develop platform-specific ad visuals.

Create API reference documentation from docstrings. Use when documenting public module interfaces.

Generates test files following TDD patterns with Given-When-Then structure. Use when creating tests for domain logic, API endpoints, or repositories.

Create starter code from templates. Use when setting up new modules or test files.

Generate the comprehensive demo markdown artifacts from the current codebase. Use before UAT to ensure test artifacts reflect the latest code.

Generate an end-to-end test for a given feature or user story. Use when the user asks to create E2E tests, automate workflows, test user flows, or convert manual workflows into Playwright tests. Leverages Playwright MCP to perform the workflow interactively before generating test code.

Auto-generate test data factories from schemas, types, or models. Use when creating test data infrastructure, setting up fixtures, or reducing test setup boilerplate.

Generates features_spec.txt files for use with auto-code extension mode. Analyzes existing codebase and creates structured feature specifications based on user requirements.

Generate Django database migrations for Sentry. Use when creating migrations, adding/removing columns or tables, adding indexes, or resolving migration conflicts.

Homeostatic actuator auto-generating missing tests for requirements with low coverage. Creates unit tests, edge cases, and error cases for REQ-* without sufficient test coverage. Use when validate-test-coverage detects gaps.

Generates three project-specific behavioral mode skills (planner, debugger, qa-tester) from project memories and bundled templates, and makes them selectable via switching-modes. Use when creating project-local agent modes for a repository.

Create the deliverable (code, documentation, tests, content) following the user's standards and best practices. Use after validation passes to actually build the work product.

Generate QA test cases in Traditional Chinese from project code analysis.

Generate Mos Sparkle appcast.xml from the latest build zip and recent git changes (since a given commit), then sync to docs/ for publishing.

generate-spec

Generate specialized skills for each subsystem in the monorepo. Creates shared language skills and subsystem-specific checklists for high-quality AI code generation.

Generate comprehensive test cases from specification documents using AI in the QuickRail project. Use when users want to create test cases from requirements, spec documents, or feature descriptions. Supports both Web UI and API-based generation with customizable prompts and context engineering.

Create comprehensive unit test plans for Swift code with TDD methodology. Use this when planning tests for new features, ensuring test coverage, creating test checklists, or implementing Test-Driven Development practices.

Generate Jest test suite with mocks and common test cases. Use when creating tests for components, repositories, or API routes.

Generate comprehensive tests for code. Use when adding test coverage, implementing TDD, or ensuring code reliability.

Generate job-targeted CV variants with built-in quality gates. Queries knowledge base, customizes content, runs eval/redteam pipeline.

Create a new artifact (text, code, plan, data) under specified constraints. Use when producing content, writing code, designing solutions, or synthesizing outputs.

Generate images using AI models via OpenRouter API. Supports text-to-image and image-based generation with customizable aspect ratios. Use when the user asks to generate, create, or synthesize images based on text descriptions or reference images.

Generates MAID snapshot JSON for agent inspection visualization. Use when asked to create snapshot data, export agent traces, or generate JSON for the MAID inspection panel.