developing-genkit-tooling
Best practices for authoring Genkit tooling, including CLI commands and MCP server tools. Covers naming conventions, architectural patterns, and consistency guidelines.
Install
With your agent
Install OMGSkills skill "firebase/genkit:developing-genkit-tooling" into this agent's normal skills directory: call the OMGSkills MCP get_install_plan tool for your agent and run the script it returns (it installs only the pinned commit and verifies SKILL.md), and stop if MCP or the pin is unavailable. Do not overwrite or change existing skills without asking me.
Manual command
git clone https://github.com/genkit-ai/genkit /tmp/genkit && ln -s /tmp/genkit/skills/developing-genkit-tooling ~/.claude/skills/developing-genkit-toolingFrom README
Developing Genkit Tooling Naming Conventions Consistency in naming helps users and agents navigate the tooling. CLI Commands Use kebab-case with colon separators for subcommands. Format: noun:verb or category:action Examples: flow:run, eval:run, init Arguments: Use camelCase in code (flowName) but standard format in help text ( ). MCP Tools Use snakecase for tool names to align with MCP standards. Format: verbnoun Examples: listflows, runflow, listgenkitdocs, readgenkitdocs CLI Command Architecture Commands are implemented in cli/src/commands/ using commander. Runtime Interaction Most commands require interacting with the user's project runtime. Use the runWithManager utility to handle the lifecycle of the runtime process. Output Formatting Logging: Use logger from @genkit-ai/tools-common/utils. Machine Readable: Provide options for JSON output or file writing when the command produces data.
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