agents-cli is a command-line tool and collection of skills that guides coding assistants through building, evaluating, and deploying AI agents on Google's Gemini Enterprise Agent Platform. Developers use it with assistants such as Claude Code, Codex, and Antigravity CLI to work with Google Cloud agent services. The catalogue entries provide skills and a plugin for that development workflow.
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.
npx skills add google/agents-cli --skill google-agents-cli-scaffoldgit clone --depth 1 https://github.com/google/agents-cliWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/google/agents-cli/google-agents-cli-scaffold)<a href="https://agentmods.dev/skills/google/agents-cli/google-agents-cli-scaffold"><img src="https://agentmods.dev/badge/skills/google/agents-cli/google-agents-cli-scaffold/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/google/agents-cli/google-agents-cli-scaffold"><img src="https://agentmods.dev/badge/skills/google/agents-cli/google-agents-cli-scaffold.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 208 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 103 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 103 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 108 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00135 | $0.03129 |
| Opus 5.5 | $0.00054 | $0.01252 |
| Sonnet 5.5 | $0.00027 | $0.00626 |
| Haiku 4.5 | $0.00014 | $0.00313 |
Grade A, and why
google-agents-cli-scaffold 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.
How it starts
The opening of the file, as written. The whole thing — 278 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project Scaffolding Guide
Requires:
agents-cli(uv tool install google-agents-cli) — install uv first if needed.
Use the agents-cli CLI to create new agent projects or enhance existing ones with deployment, CI/CD, and infrastructure scaffolding.
Prerequisite: Clarify Requirements (MANDATORY for new projects)
Before scaffolding a new project, load /google-agents-cli-workflow and complete Phase 0 — clarify the user's requirements before running any scaffold create command. Ask what the agent should do, what tools/APIs it needs, and whether they want a prototype or full deployment.
Step 1: Choose Architecture
Mapping user choices to CLI flags:
| Choice | CLI flag |
|---|---|
| Retrieval/RAG, sandboxed execution, cross-session memory, OAuth consent, guardrails, scheduled runs | No flag — these come from clone-and-study recipes. ADK Python: see the topic index in /google-agents-cli-adk-code → references/samples.md; on other frameworks, see the sample index the framework template ships |
| A2A protocol | built into the scaffolded app — scaffold normally (ADK Python: --agent adk, the default; ADK Go: --agent adk_go) |
| Prototype (no deployment) | --prototype |
| Deployment target | --deployment-target <agent_runtime|cloud_run|gke> |
| CI/CD runner | --cicd-runner <github_actions|google_cloud_build> |
| Session storage | --session-type <in_memory|cloud_sql|agent_platform_sessions> |
Product name mapping
Current names (and older names users may say) → CLI values (vertexai SDK package name unchanged):
- Agent Runtime in Gemini platform (Agent Engine / Vertex AI Agent Engine / Agent Runtime) →
--deployment-target agent_runtime - Sessions in Gemini platform (Agent Engine sessions / Agent Platform Sessions) →
--session-type agent_platform_sessions - Search / Vector Search in Gemini platform (Vertex AI Search / Vertex AI Vector Search) / RAG → clone-and-study recipe, not a flag
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago Changed aba1a37a719f
- 9d ago Changed 9ded836b3b73
- 15d ago Changed · +4 lines 75f42a12e143
- 23d ago Changed · +4 lines ad48e0f7aecb
- 29d ago Changed · +18 lines 68fb0103ce61
- 1mo ago Changed · +4 lines · -2 tokens per session e574ded4906e
- 1mo ago First seen · 248 lines · 137 tokens per session scan A 996dbc6df215
google-agents-cli-scaffold is a skill published in the GitHub repository google/agents-cli (6,094 stars, last pushed 3d ago), licensed Apache-2.0. It adds 135 tokens to every session and 3,129 once invoked, about $0.0005 per session on Opus 5.5. 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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