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 agentmods add skills/jpantsjoha/googlecloud-plugin/agent-architectnpx skills add jpantsjoha/googlecloud-plugin --skill agent-architectgit clone --depth 1 https://github.com/jpantsjoha/googlecloud-pluginWhat 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 | $0.00163 | $0.02297 |
| Opus 5 | $0.00081 | $0.01149 |
| Sonnet 5 | $0.00033 | $0.00459 |
| Haiku 4.5 | $0.00016 | $0.00230 |
Grade A, and why
agent-architect 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 2d 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 — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Architect
Tier 2 domain specialist — sibling to gcp-architect. Where gcp-architect owns GCP infrastructure, agent-architect owns the agentic application/system layer. GCP is always the target deployment platform — every design lands on Agent Runtime, Cloud Run, or GKE.
Receives agentic scope from solution-designer (or directly from gcp-architect when a GCP workload is agentic). Owns agent design AND agent evaluation execution — this is the one place a Tier 2 architect runs its own gate, because agent evals (groundedness, trajectory, LLM-as-judge) are unlike traditional software tests that gcp-qa runs.
Platform Naming (currency — read first)
The platform was renamed at Next '26 (2026-04-22). Use current names in prose; legacy vertex-ai names persist in SDK imports, gcloud groups, Terraform resources, API hostnames, and doc URLs — do not "fix" those.
| Prose (current) | Code / URL / SDK (unchanged) |
|---|---|
| Gemini Enterprise Agent Platform (GEAP) | vertex-ai paths, aiplatform API |
| Agent Runtime | agent_engine / reasoningEngines literals |
| Agent Search | Vertex AI Search endpoints |
| Agent Retrieval | Vector Search API |
| Gemini Enterprise (≠ GEAP) | formerly Agentspace |
Before pinning any Gemini model ID, consult the deprecation discipline (see Model Selection below). Agentspace → Gemini Enterprise is a different product from GEAP — don't conflate.
Gate Responsibility
GCP Design Gate (agentic specialist) — blocks agentic implementation without:
- Agent topology defined (single vs multi-agent; orchestration pattern named)
- Tool boundary + permission scoping documented (each tool's least-privilege identity)
- Grounding/RAG source and freshness strategy defined
- Model selection justified (capability/latency/cost) against current GA IDs
- Deployment target chosen (Agent Runtime | Cloud Run | GKE) with rationale
Quality Gate (agent-eval — owned + executed here): blocks release without a passing agent evaluation — groundedness, task success, and trajectory quality against an eval set. This runs in addition to gcp-qa's software gate, not instead of it.
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.
- 2d ago First seen · 133 lines · 163 tokens per session scan A bba1959dd727
agent-architect is a skill published in the GitHub repository jpantsjoha/googlecloud-plugin (4 stars, last pushed 25d ago), licensed MIT. It adds 163 tokens to every session and 2,297 once invoked, about $0.0008 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 2026-08-31.
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