Official agent skill

Google Cloud Solution Multi Agent Security

by google in google/skills

Designs, deploys, and secures Google Cloud Agent Gateway solutions.

OfficialApache-2.0Auto-check passedDevOps & Cloud

Install Google Cloud Solution Multi Agent Security

skills CLI
$ npx skills add google/skills --skill google-cloud-solution-multi-agent-security -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install google/skills google-cloud-solution-multi-agent-security --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/cloud/google-cloud-solution-multi-agent-security .claude/skills/google-cloud-solution-multi-agent-security && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
google-cloud-solution-multi-agent-security
GitHub stars
21k
Token cost
~3.7k tokens
SKILL.md length
1,189 words
Files
23 (incl. scripts, assets)
Skills in repo
145
Repo updated
First seen
Licence
Apache-2.0

At a glance

Designs, deploys, and secures Google Cloud Agent Gateway solutions.

  • Works in 11 steps: Dual Ingress & Egress Architecture… → Ingress & Egress Guardrail Policy Config… → Ingress & Egress Infrastructure… → …
  • The user needs to configure multi-agent security
  • SKILL.md covers Critical Enforcement Rules &…, Quick Reference: Required…, 1. Dual Ingress & Egress… and 2. Ingress & Egress Guardrail…, plus 9 more sections
  • Runs Shell and Python scripts from its folder; calls gcloud

What it does

Google Cloud Solution Multi Agent Security is an agent skill from google/skills, published by the product's own GitHub organization. Designs, deploys, and secures Google Cloud Agent Gateway solutions. Use when the user needs to configure multi-agent security, ingress (CLIENTTOAGENT), or egress (AGENTTOANYWHERE) patterns involving Model Armor, IAP, and Agent Registry. Don't use for general Cloud Load Balancing or basic VPC setup not related to Agent Gateways.

Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 24 other files, including scripts and assets (for example `assets/agw-authz-extension.yaml`, `assets/agw-authz-policy.yaml` and `assets/agw-egress-config-run.yaml`).

It sits in DevOps & Cloud, covering Cloud networking and Multi-agent orchestration. It works with Google Cloud. The repository describes itself as: Agent Skills for Google products and technologies. The licence is Apache-2.0.

When your agent uses it

  • The user needs to configure multi-agent security
  • Ingress (CLIENTTOAGENT)
  • Egress (AGENTTOANYWHERE) patterns involving Model Armor
  • General Cloud Load Balancing

Example prompts

  • “/google-cloud-solution-multi-agent-security”

Requirements

  • Python 3
  • A Bash shell

Workflow steps

11 steps, taken from the step headings in SKILL.md.

  1. Dual Ingress & Egress Architecture Design (dual_ingress_egress_architecture_design)
  2. Ingress & Egress Guardrail Policy Config (ingress_and_egress_guardrail_policy_config)
  3. Ingress & Egress Infrastructure Deployment (ingress_and_egress_infrastructure_deployment)
  4. Ingress & Egress Security Validation (ingress_and_egress_security_validation)
  5. Troubleshooting Ingress & Egress Failures (troubleshooting_ingress_and_egress_failures)
  6. Hybrid VPN Connectivity & Egress Routing (hybrid_vpn_connectivity_egress_routing)
  7. Private Egress GKE Internal Load Balancer (private_egress_gke_internal_load_balancer)
  8. Governance Controls Model Armor SGP (governance_controls_model_armor_sgp)
  9. Multi-Agent Cloud Run Egress Routing (multi_agent_cloud_run_egress_routing)
  10. Advanced Model Armor Filtering (advanced_model_armor_filtering)
  11. Known Traps & Gotchas (known_traps_and_gotchas)

What it can do on your machine

Read from SKILL.md and the folder at commit 8a1ac05. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 6 files in scripts/ (Shell and Python, from the files we listed), which the agent can run.

    Shell commands in SKILL.md call:

    • gcloud

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use gcloud, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Google Cloud Solution Multi Agent Security loads about 3.7k tokens when it runs. Until then it costs about 94 tokens; SKILL.md has 1,189 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~94
When it runs · the whole SKILL.md, loaded when a task matches
~3.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from google/skills at commit 8a1ac05, republished under its Apache-2.0 licence (© google). 1,189 words, ~3,695 tokens.

Download SKILL.mdSave it as .claude/skills/google-cloud-solution-multi-agent-security/SKILL.md (or your agent's skills folder). This skill also uses 22 other files; get the full folder from GitHub.
name
google-cloud-solution-multi-agent-security
description
Designs, deploys, and secures Google Cloud Agent Gateway solutions. Use when the user needs to configure multi-agent security, ingress (CLIENT_TO_AGENT), or egress (AGENT_TO_ANYWHERE) patterns involving Model Armor, IAP, and Agent Registry. Don't use for general Cloud Load Balancing or basic VPC setup not related to Agent Gateways.
metadata.version
1.0.0
metadata.category
MultiProductSolutions

Agent Gateway multi-agent security

Critical Enforcement Rules & Rationale

  • Gcloud Release Tracks: Always use the exact release tracks specified in the commands (e.g., gcloud beta network-services agent-gateways). Omitting these prefixes causes commands to fail because Agent Gateway features are located in specialized, non-default namespaces.
  • API Enablement: Include modelarmor.googleapis.com in the API enablement list when setting up guardrails. Excluding it prevents Model Armor policies and filters from successfully attaching to the Gateway.
  • Egress Verification: Egress policy verification requires using the Python script (scripts/verify_egress_policies.py), not curl. Egress gateways rely on runtime SDK lifecycle handling and JWT context that a standard curl command cannot simulate correctly.
  • Model Armor Keys: In model-armor-config.yaml, always include both piAndJailbreakFilterSettings and sdpFilterSettings (filterEnforcement: ENFORCE). Invalid or missing filters cause deployment validation failures or lead to silent bypasses of the guardrails.
  • Subnet Private Access: Any subnet hosting a Private Service Connect network attachment for Egress Gateways must have private_ip_google_access = true enabled in Terraform. Disabling this blocks connectivity to Google-managed endpoints, causing total routing failures for agents.
  • Direct Delivery: Immediately provide the requested architecture, configuration files, CLI commands, scripts, and diagrams in full. Do not stop at a planning phase, do not generate a plan artifact, and do not ask for user confirmation before delivering outputs.
  • No Infrastructure Execution: Do not attempt to run deployment or verification commands (such as gcloud, kubectl, terraform, or curl) against real cloud resources during design. You are generating plan configurations, not executing them.

[!IMPORTANT] Just-In-Time (JIT) Resource Loading Protocol: Inspect template files in assets/ and executable scripts in scripts/ using view_file as needed for extended configurations, deployment scripts, and test suites.


Quick Reference: Required Filenames

Always generate files with these exact names when requested:

  1. agw-ingress-config.yaml (assets/agw-ingress-config.yaml)
  2. agw-egress-config.yaml (assets/agw-egress-config.yaml)
  3. agw-authz-extension.yaml (assets/agw-authz-extension.yaml)
  4. agw-authz-policy.yaml (assets/agw-authz-policy.yaml)
  5. model-armor-config.yaml (assets/model-armor-config.yaml)
  6. sgp-policy.yaml (assets/sgp-policy.yaml)
  7. iap-policy.json (assets/iap-policy.json)
  8. model-armor-payload.json (assets/model-armor-payload.json)

1. Dual Ingress & Egress Architecture Design (dual_ingress_egress_architecture_design)

  • Ingress Pattern: CLIENT_TO_AGENT fronted by Ingress Control Plane (Agent Gateway, Model Armor).

  • Egress Pattern: AGENT_TO_ANYWHERE utilizing Egress Control Plane (Agent Gateway, roles/iap.egressor CEL policies, Cloud DNS) and Egress Data Plane (PSC Interface, Cloud Run, PSC Google APIs Global Endpoint), coordinated via Agent Registry & Agent Engine runtime.

  • Mermaid Diagram:

    mermaid
    graph TD
        Client["External Clients"] -->|HTTPS / MCP| GLB["Global Load Balancer"]
        GLB --> Ingress["Ingress Agent Gateway (CLIENT_TO_AGENT)"]
        Ingress --> MA["Model Armor (CONTENT_AUTHZ)"]
        MA --> Agent["Agent Engine Agents (BillingAgent, SupportAgent, FraudAgent)"]
        Agent --> Egress["Egress Agent Gateway (AGENT_TO_ANYWHERE)"]
        Egress --> PSC["Private Service Connect Network Attachment"]
        PSC --> Tools["Private MCP Tool Backends"]

2. Ingress & Egress Guardrail Policy Config (ingress_and_egress_guardrail_policy_config)

When requested for Ingress & Egress guardrail policy configs, you MUST generate and create all required files in the workspace:

  • agw-ingress-config.yaml (assets/agw-ingress-config.yaml): Declares governedAccessPath: CLIENT_TO_AGENT with protocols HTTP and MCP.
  • agw-egress-config.yaml (assets/agw-egress-config.yaml): Declares governedAccessPath: AGENT_TO_ANYWHERE with protocol MCP.
  • agw-authz-extension.yaml (assets/agw-authz-extension.yaml): Configures AuthzExtension service for IAP authorization.
  • agw-authz-policy.yaml (assets/agw-authz-policy.yaml): Configures AuthzPolicy action ALLOW targeting both Ingress and Egress gateways.
  • iap-policy.json (assets/iap-policy.json): Binds roles/iap.egressor with CEL condition checking iap.googleapis.com/mcp.toolName == 'get_account_balance' && iap.googleapis.com/mcp.tool.isReadOnly == true.
  • model-armor-config.yaml (assets/model-armor-config.yaml): Enables piAndJailbreakFilterSettings and sdpFilterSettings with filterEnforcement: ENFORCE.
  • sgp-policy.yaml (assets/sgp-policy.yaml): Implements Natural Language Constraints blocking transactions > $1000 and sanitizing PII.

3. Ingress & Egress Infrastructure Deployment (ingress_and_egress_infrastructure_deployment)

Inspect and provide the step-by-step gcloud CLI commands from scripts/deploy_infrastructure.sh:

  1. Enable Required APIs: compute, networkservices, networksecurity, modelarmor, iap, agentregistry, serviceextensions, and aiplatform.
  2. Import Agent Gateways: Ingress (agw-ingress-config.yaml) and Egress (agw-egress-config.yaml) via gcloud alpha network-services agent-gateways import.
  3. Import Authz Extension: agw-authz-extension.yaml via gcloud beta service-extensions authz-extensions import.
  4. Import Authz Policy: agw-authz-policy.yaml via gcloud beta network-security authz-policies import.

4. Ingress & Egress Security Validation (ingress_and_egress_security_validation)

When validating security for Ingress and Egress:

  1. Ingress 403 Unauthenticated Test: Provide the copy-pasteable verification curl command from scripts/validate_ingress_unauth.sh sending an unauthenticated POST request to the Reasoning Engine endpoint expecting HTTP 403 Forbidden.
  2. Python Egress Verification Script (MUST use Python script snippet, NOT curl): Provide the Python verification script snippet from scripts/verify_egress_policies.py sending JSON-RPC tools/call requests (get_account_balance) through the Egress Gateway to verify HTTP 200 for allowed tools.
  3. Model Armor Test Payload: Generate model-armor-payload.json (assets/model-armor-payload.json) containing prompt injection/jailbreak instructions.

5. Troubleshooting Ingress & Egress Failures (troubleshooting_ingress_and_egress_failures)

  • Ingress 403 (Client-to-Agent):

    • Root Cause: Unauthenticated client requests or missing/invalid OAuth 2.0 / IAP identity tokens.
    • OAuth Configuration Steps:
      1. Configure OAuth 2.0 Client ID credentials in Google Cloud Console.
      2. Grant the client identity / service account roles/iap.httpsResourceAccessor permission.
      3. Exchange credentials with Google OAuth to acquire an OIDC / OAuth ID token.
      4. Pass the token in the Authorization: Bearer <TOKEN> header.
    • Verification Command: Provide the curl command from scripts/verify_ingress_auth.sh.
  • Egress 403 (Agent-to-Anywhere):

    • Root Cause: Missing roles/iap.egressor IAM bindings on the Agent Identity, malformed principal ID, or mismatched CEL condition on tool metadata.
    • Fix Command: Provide the exact gcloud command from scripts/fix_egress_iap.sh.

Show full SKILL.md (431 more words)Show less

6. Hybrid VPN Connectivity & Egress Routing (hybrid_vpn_connectivity_egress_routing)

  • Terraform HCL: Refer to baseline Terraform config in assets/main.tf for VPC, subnets (private_ip_google_access = true), PSC network attachment, Cloud DNS private forwarding for aws.internal., and HA VPN gateway/router.
  • Egress Gateway Config (agw-egress-config.yaml): Generate configuration declaring governedAccessPath: AGENT_TO_ANYWHERE, pointing to the PSC network attachment, and referencing aws.internal. in dnsPeeringConfig (see assets/agw-egress-config.yaml).
  • Python SDK Deployment Script: Refer to scripts/hybrid_vpn_agent.py for the complete script initializing Vertex AI with agent_to_anywhere_config referencing the Egress Gateway, enabling telemetry, and deploying HybridAgent using types.IdentityType.AGENT_IDENTITY.

7. Private Egress GKE Internal Load Balancer (private_egress_gke_internal_load_balancer)

  • Expose GKE internal MCP tool server via an Internal Load Balancer (ILB) at literal IP 10.0.1.50, connecting via Agent Gateway PSC Interface + Cloud DNS Private zone.
  • Cloud DNS Record Mapping: Provide the command from scripts/create_gke_dns_record.sh mapping the private domain to GKE's private ILB IP 10.0.1.50.
  • Explicit TLS Warning: Agent Gateway egress does not natively trust self-signed certificates or private enterprise CAs. You must use publicly trusted TLS certificates signed by a trusted Certificate Authority (e.g., Let's Encrypt).

8. Governance Controls Model Armor SGP (governance_controls_model_armor_sgp)

When configuring dual safety layers with Model Armor on Ingress and SGP on Egress:

  1. Model Armor Config: Generate model-armor-config.yaml (assets/model-armor-config.yaml) with piAndJailbreakFilterSettings and sdpFilterSettings (filterEnforcement: ENFORCE).
  2. Semantic Governance Policy: Generate sgp-policy.yaml (assets/sgp-policy.yaml) with Natural Language Constraints blocking transactions > $1000 and sanitizing PII.
  3. Curl PATCH Command: Provide the curl command from scripts/enforce_sgp_patch.sh to update authzExtensions with sgpEnforcementMode set to ENFORCE.

9. Multi-Agent Cloud Run Egress Routing (multi_agent_cloud_run_egress_routing)

Do NOT produce a plan artifact or stop at planning. When configuring multi-agent Cloud Run egress routing, you MUST directly provide and generate ALL required components:

  1. Egress Gateway Config (agw-egress-config-run.yaml): Generate configuration declaring governedAccessPath: AGENT_TO_ANYWHERE, PSC network attachment, and DNS peering for *.run.app (see assets/agw-egress-config-run.yaml).
  2. Register Cloud Run Services in Agent Registry: Provide the registration commands from scripts/register_cloud_run_services.sh registering all 3 Cloud Run services (marketing-tool-service, sales-tool-service, support-tool-service) in the us-east4 Agent Registry.
  3. iap-policy.json (Multi-Agent): Generate iap-policy.json (assets/iap-policy-multi-agent.json) containing all 3 principal:// bindings in the members list under roles/iap.egressor.
  4. Python SDK Deployment Script: Refer to scripts/multi_agent_cloud_run.py for the complete GenAI SDK deployment script.

10. Advanced Model Armor Filtering (advanced_model_armor_filtering)

For custom keyword matching, configure userDefinedFilterSettings (see assets/model-armor-advanced.yaml).


11. Known Traps & Gotchas (known_traps_and_gotchas)

  • network_attachment is ForceNew: Enabling Semantic Governance Policies (SGP) or modifying network attachments after the initial Terraform apply will force-recreate the gateway resource. If not managed carefully, this can cause dependency deadlocks during destroy operations. Plan infrastructure sequencing accordingly.
  • Authz Policy Limit: An Agent Gateway allows at most 4 custom authorization policies attached concurrently. Ensure your security posture consolidates rules within this limit.

© google, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 22 other files (scripts, assets) in skills/cloud/google-cloud-solution-multi-agent-security of google/skills.

  • SKILL.md
  • assets/agw-authz-extension.yaml
  • assets/agw-authz-policy.yaml
  • assets/agw-egress-config-run.yaml
  • assets/agw-egress-config.yaml
  • assets/agw-ingress-config.yaml
  • assets/iap-policy-multi-agent.json
  • assets/iap-policy.json
  • assets/main.tf
  • assets/model-armor-advanced.yaml
  • assets/model-armor-config.yaml
  • assets/model-armor-payload.json
  • assets/sgp-policy.yaml
  • scripts/create_gke_dns_record.sh
  • scripts/deploy_infrastructure.sh
  • scripts/enforce_sgp_patch.sh
  • scripts/fix_egress_iap.sh
  • scripts/hybrid_vpn_agent.py
  • scripts/multi_agent_cloud_run.py
  • … and 4 more

Open the folder on GitHubat commit 8a1ac05

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GCP Cloud Loggingautomateyournetwork/netclaw674—~1.6kAutomated safety check: PassApache-2.0

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Works with

Questions about Google Cloud Solution Multi Agent Security

What does Google Cloud Solution Multi Agent Security do?

Designs, deploys, and secures Google Cloud Agent Gateway solutions. Google Cloud Solution Multi Agent Security is an agent skill from google/skills, published by the product's own GitHub organization. Designs, deploys, and secures Google Cloud Agent Gateway solutions.

When should I use Google Cloud Solution Multi Agent Security?

Google Cloud Solution Multi Agent Security fits situations like: the user needs to configure multi-agent security; ingress (CLIENTTOAGENT); egress (AGENTTOANYWHERE) patterns involving Model Armor; general Cloud Load Balancing.

How do I install Google Cloud Solution Multi Agent Security in Claude Code?

Run `npx skills add google/skills --skill google-cloud-solution-multi-agent-security -a claude-code`. Or copy the skill folder (skills/cloud/google-cloud-solution-multi-agent-security in google/skills) into .claude/skills/google-cloud-solution-multi-agent-security in your project. Claude Code loads it when a task matches its description.

How do I install Google Cloud Solution Multi Agent Security in Codex?

Run `npx skills add google/skills --skill google-cloud-solution-multi-agent-security -a codex`. Or copy the skill folder (skills/cloud/google-cloud-solution-multi-agent-security in google/skills) into .agents/skills/google-cloud-solution-multi-agent-security in your project. Codex loads it when a task matches its description.

Can I use Google Cloud Solution Multi Agent Security in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add google/skills --skill google-cloud-solution-multi-agent-security -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/google-cloud-solution-multi-agent-security, .gemini/skills/google-cloud-solution-multi-agent-security, .github/skills/google-cloud-solution-multi-agent-security and .opencode/skills/google-cloud-solution-multi-agent-security in your project.

What does Google Cloud Solution Multi Agent Security need to run?

Going by SKILL.md and its folder, Google Cloud Solution Multi Agent Security needs a shell and Python for the scripts in its folder and the command-line tools its instructions call (gcloud). Our summary lists: Python 3; A Bash shell.

Does Google Cloud Solution Multi Agent Security access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Google Cloud Solution Multi Agent Security safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Google Cloud Solution Multi Agent Security use?

Google Cloud Solution Multi Agent Security is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Google Cloud Solution Multi Agent Security use?

About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Google Cloud Solution Multi Agent Security?

Skills that share tags, products or a category with Google Cloud Solution Multi Agent Security: Dangling DNS Finder (anirudhbiyani/findmytakeover, 180 stars), Intrinsic Core Concepts (intrinsic-ai/intrinsic-core, 552 stars), GCP Networking (sickn33/agentic-awesome-skills, 47k stars) and Implementing GCP Vpc Firewall Rules (mukul975/Anthropic-Cybersecurity-Skills, 34k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Google Cloud Solution Multi Agent Security?

google (a GitHub organization, an official publisher) maintains it in google/skills, which has 20,994 GitHub stars. The repository holds 145 skills in this directory. The repository was last updated on October 6, 2026.

Source: google/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.