google-agents-cli-workflow
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How to install google-agents-cli-workflow?
google/agents-cli/google-agents-cli-workflow
$npx -y skills add google/agents-cli --skill google-agents-cli-workflowgoogle-agents-cli-workflow is an agent skill published from google/agents-cli, installable through the skills CLI.
SKILL.md
| 1 | # Agent Development Workflow & Guidelines |
| 2 | |
| 3 | **agents-cli** is a CLI and skills toolkit for building, evaluating, and deploying agents on Google Cloud. It works with any coding agent — Antigravity CLI, Claude Code, Codex, or others — and with the agent framework of your choice (the [Agent Development Kit (ADK)](https://adk.dev/) by default). Install with `uvx google-agents-cli setup`. |
| 4 | |
| 5 | > **Before writing agent code, make sure a scaffolded project exists (see Phase 2).** Skipping scaffolding loses eval boilerplate, CI/CD config, and project conventions. |
| 6 | |
| 7 | |
| 8 | > Requires: google-agents-cli ~= 1.1.0 |
| 9 | > If version is behind, run: uv tool install "google-agents-cli~=1.1.0" |
| 10 | |
| 11 | > Check version: agents-cli info |
| 12 | > [Install uv](https://docs.astral.sh/uv/getting-started/installation/index.md) first if needed. |
| 13 | |
| 14 | ## Session Continuity & Skill Cross-References |
| 15 | |
| 16 | Re-read the relevant skill **before** each phase — not after you've already started and hit a problem. Context compaction may have dropped earlier skill content. If skills are not available, run `uvx google-agents-cli setup` to install them. |
| 17 | |
| 18 | | Phase | Skill | When to load | |
| 19 | |-------|-------|--------------| |
| 20 | | 0 — Understand | — | No skill needed — read `.agents-cli-spec.md` if present, else clarify goals with the user | |
| 21 | | 1 — Study samples | — | Check the Notable Samples catalog in `references/samples.md` — clone and study matching samples before scaffolding | |
| 22 | | 2 — Scaffold | `/google-agents-cli-scaffold` | Before creating or enhancing a project | |
| 23 | | 3 — Build | `/google-agents-cli-adk-code` | Before writing agent code — API patterns, tools, callbacks, state | |
| 24 | | 4 — Evaluate | `/google-agents-cli-eval` | Before running any eval — dataset schema, metrics, eval-fix loop | |
| 25 | | 5 — Deploy | `/google-agents-cli-deploy` | Before deploying — target selection, troubleshooting 403/timeouts | |
| 26 | | 6 — Publish | `/google-agents-cli-publish` | After deploying, if registering with Gemini Enterprise (optional) | |
| 27 | | 7 — Observe | `/google-agents-cli-observability` | After deploying — traces, logging, monitoring setup | |
| 28 | |
| 29 | --- |
| 30 | |
| 31 | ## Setup |
| 32 | |
| 33 | If `agents-cli` is not installed: |
| 34 | ```bash |
| 35 | uv tool install google-agents-cli |
| 36 | ``` |
| 37 | |
| 38 | ### `uv` command not found |
| 39 | |
| 40 | Install `uv` following the [official installation guide](https://docs.astral.sh/uv/getting-started/installation/index.md). |
| 41 | |
| 42 | ### Product name mapping |
| 43 | |
| 44 | Users name products inconsistently (Vertex AI → Agent Platform, Agent Engine → Agent Runtime, etc.). Map user terms to CLI values using `references/terminology.md`. |
| 45 | |
| 46 | --- |
| 47 | |
| 48 | ## Phase 0: Understand |
| 49 | |
| 50 | Before writing or scaffolding anything, understand what you're building — through a **design dialogue**, not a checklist. Load `references/brainstorming.md` and follow it: ask **one question at a time**, propose 2–3 architecture approaches for non-trivial agents, and validate the design before any scaffolding. |
| 51 | |
| 52 | If `.agents-cli-spec.md` exists in the current directory, read it — it is your primary source of truth. Otherwise: |
| 53 | |
| 54 | Do NOT proceed to planning, scaffolding, or coding until the user approves the spec. Do not assume, research, or fill in the blanks yourself — the user's intent drives everything. |
| 55 | |
| 56 | **Scale the ceremony to complexity:** a trivial agent (single tool, fixed persona) needs only a couple of questions, a 2–3 sentence spec, and one approval; a complex agent (multi-agent, RAG, external APIs/auth, safety-critical) gets the full treatment in `references/brainstorming.md`. |
| 57 | |
| 58 | **Topics to cover** (one question at a time, adapting to the user — see the playbook): |
| 59 | |
| 60 | 1. **What problem will the agent solve?** — Core purpose and capabilities |
| 61 | 2. **External APIs or data sources needed?** — Tools, integrations, auth requirements |
| 62 | 3. **Safety constraints?** — What the agent must NOT do, guardrails |
| 63 | 4. **Deployment preference?** — Prototype first (recommended) or full deployment? If deploying: Agent Runtime, Cloud Run, or GKE? |
| 64 | |
| 65 | **Ask based on context:** |
| 66 | |
| 67 | - If the agent needs **retrieval/search over data** (RAG, semantic/vector search, embeddings) → RAG is a **clone-and-study recipe**, not a scaffold flag. In Phase 1, study `rag-vector-search` (embeddings / similarity search) or `rag-agent-search` (managed document search) from `references/samples.md` and adapt o |
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