Google Agents Cli Adk CodeSAFE

The CLI and skills that turn any coding assistant into an expert at creating, evaluating, and deploying AI agents on Google Cloud.

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: google-agents-cli-adk-code
description: >
  This skill should be used when the user wants to "write agent code",
  "build an agent with ADK", "add a tool", "create a callback", "define an agent",
  "use state management" — in a project that needs ADK (Agent Development Kit) API
  patterns and code examples.
  It provides a quick reference for agent types, tool definitions, orchestration
  patterns, callbacks, state management, the graph Workflow API, and reference
  recipes to study.
  Do NOT use for scaffolding (use google-agents-cli-scaffold) or deployment
  (use google-agents-cli-deploy).
metadata:
  author: Google
  license: Apache-2.0
  version: 1.11.0
  requires:
    bins:
      - agents-cli
    install: "uv tool install google-agents-cli"
---

# ADK Code Reference

Activate `/google-agents-cli-workflow` first for required development phases and scaffolding steps.

## 1. Study Recipes (No Project Needed)

**Python — read the topic index in `references/samples.md` before answering "how do I build X".**
Worked implementations exist for: sandboxed/per-user code execution, agent-loadable `SKILL.md`
skills, cross-session memory, approval gates before risky actions, tool guardrails, per-user
credentials, and scheduled/event-driven runs.

**Go — read the upstream [`examples/`](https://github.com/google/adk-go/tree/main/examples).**
clone the repo and read the one matching the capability you need before implementing it.

## 2. Prerequisites for Writing Code

Do NOT write agent code until a project is scaffolded.

1. Verify project: run `agents-cli info` (proceed if config exists).
2. New project: run `agents-cli scaffold create <name> --agent adk --deployment-target <target>` — use `--agent adk_go` for Go.
3. Existing code: run `agents-cli scaffold enhance .`.

## Quick Reference — Most Common Patterns

See `references/adk-python.md` and `references/adk-go.md` for Python and Go code examples, respectively.

---

## References

Use the cheatsheets for common patterns. For deep knowledge, fetch the docs index or inspect the
installed package.

| Reference | Language | When to read |
|------|------|-------------|
| `references/samples.md` | Python | **Topic-indexed catalog of ADK reference recipes.** Read in workflow Phase 1 — before scaffolding and before writing code — maps a capability to the recipe that implements it. |
| `references/adk-python.md` | Python | Core ADK API: `Agent`, tools, callbacks, plugins, state, artifacts, multi-agent systems, `SequentialAgent` / `ParallelAgent` / `LoopAgent`, custom `BaseAgent`, `ManagedAgent` (server-hosted first-party agents), A2A protocol, A2UI. Default for most agents. |
| `references/adk-python-workflows.md` | Python | Graph-based Workflow API (ADK Python 2.0): nodes, edges, fan-out/fan-in, HITL, parallel processing. Use when you need explicit graph topology. |
| `references/adk-python-live.md` | Python | Live and voice agents: `Runner.run_live`, `LiveRequestQueue`, model and regional availability, voice/`speech_config`, VAD, session limits, `/run_live` serving. Use for real-time voice or video agents. |
| `references/adk-go.md` | Go | Core ADK Go API: `llmagent`, tools, callbacks, plugins, state, artifacts, multi-agent systems, sequential/parallel/loop agents, custom agents, the runner, serving over HTTP, A2A protocol, and ambient triggers. Default for most agents. |
| `references/adk-go-workflows.md` | Go | Graph-based Workflow API: nodes, edges, fan-out/fan-in, HITL, parallel processing. Use when you need explicit graph topology. |
| [`examples/`](https://github.com/google/adk-go/tree/main/examples) | Go | Runnable upstream programs — the closest thing to a recipe catalog for Go. |
| `curl https://adk.dev/llms.txt` | Python | Docs index (every page title + URL). Fetch it, then `WebFetch` the specific page for anything beyond the cheatsheets. |
| Installed ADK package | Python | Exact signatures and symbols — inspect the source (see "Inspecting ADK Source Code" in `references/adk-python.md`). |

## Related Skills

- `/google-agents-cli-workflow` — Development workflow, coding guidelines, and operational rules
- `/google-agents-cli-scaffold` — Project creation and enhancement with `agents-cli scaffold create` / `scaffold enhance`
- `/google-agents-cli-eval` — Evaluation methodology, dataset schema, and the eval-fix loop
- `/google-agents-cli-deploy` — Deployment targets, CI/CD pipelines, and production workflows

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

What the source does

Filesystem

none-observed

Network

none-observed

Shell

none-observed

Dependencies

pinned

Secrets in source

none-found

Findings (2)

BASE_URL = "http://127.0.0.1:8000"

- **Session create (HTTP):** `POST https://{LOC}-aiplatform.googleapis.com/reasoningEngines/v1/{RESOURCE}/api/apps/{APP}/users/{USER}/sessions`

Gates applied: no_behavioural_pass.

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