developing-genkit-tooling

Instructions for building Genkit command-line features and MCP tools. Genkit is a toolkit for applications that use AI models, while MCP is a standard way for an AI agent to call external tools.

In plain words
What is it for?
Use them when adding Genkit CLI commands, MCP tools, runtime interactions, logging, or command output.
Why use it?
They keep command and tool names consistent and show how to manage the project runtime while commands run.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/genkit-ai/genkit/developing-genkit-tooling
Any agent
npx skills add genkit-ai/genkit --skill developing-genkit-tooling
Clone the repo
git clone --depth 1 https://github.com/genkit-ai/genkit

Made for: Claude Code, Codex.

Per session 35 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 810 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00035 $0.00810
Opus 5 $0.00017 $0.00405
Sonnet 5 $0.00007 $0.00162
Haiku 4.5 $0.00003 $0.00081

Measured 3d ago against content hash 1eb63e6ba523, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

developing-genkit-tooling scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/developing-genkit-tooling/SKILL.md · 111 lines

How it starts

The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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 (<flowName>).

MCP Tools

Use snake_case for tool names to align with MCP standards.

  • Format: verb_noun
  • Examples: list_flows, run_flow, list_genkit_docs, read_genkit_docs

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.

import { runWithManager } from '../utils/manager-utils';

// ... command definition ...
.action(async (arg, options) => {
  await runWithManager(await findProjectRoot(), async (manager) => {
    // Interact with manager here
    const result = await manager.runAction({ key: arg });
  });
});

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.
  • Streaming: If the operation supports streaming (like flow:run), provide a --stream flag and pipe output to stdout.

MCP Tool Architecture

MCP tools in cli/src/mcp/ follow two distinct patterns: Static and Runtime.

Static Tools (e.g., Docs)

These tools do not require a running Genkit project context.

  • Registration: defineDocsTool(server: McpServer)
  • Dependencies: Only the server instance.
  • Use Case: Documentation, usage guides, global configuration.

Runtime Tools (e.g., Flows, Runtime Control)

These tools interact with a specific Genkit project's runtime.

  • Registration: defineRuntimeTools(server: McpServer, options: McpToolOptions)
  • Dependencies: Requires options containing manager (process manager) and projectRoot.
  • Schema: MUST use getCommonSchema(options.explicitProjectRoot, ...) to ensure the tool can accept a projectRoot argument when required (e.g., in multi-project environments).

Read the full file on GitHub · 111 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 111 lines · 35 tokens per session scan A 1eb63e6ba523

Subscribe to this mod's changes

developing-genkit-tooling is a skill published in the GitHub repository genkit-ai/genkit (6,389 stars, last pushed 2d ago), licensed Apache-2.0. It adds 35 tokens to every session and 810 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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