jtaroreh · Oct 23, 2026 · Oct 22, 2026 · Oct 23, 2026 · Oct 23, 2026 · Oct 23, 2026
diff --git a/README.md b/README.md
@@ -143,6 +143,25 @@ workers run in isolated containers, never push to git directly, and upload `patc
 
 set it up with [`/setup-agystack`](./skills/setup-agystack/SKILL.md) with your Google Cloud auth and run [`/swarm`](./skills/swarm/SKILL.md) to dispatch.
 
+### summoning cloud agents (Gemini & DeepSeek)
+
+Cloud swarms run on Google Cloud Run with zero-friction serverless models:
+
+```bash
+# list supported cloud models and tiers
+python3 skills/swarm/scripts/cloud_dispatch.py --list-models
+
+# fan out 5 Gemini Argon agents
+python3 skills/swarm/scripts/cloud_dispatch.py --tasks 5 --model gemini-4-argon
+
+# fan out 5 DeepSeek Flash 4.1 agents
+python3 skills/swarm/scripts/cloud_dispatch.py --tasks 5 --model deepseek-v4.1-flash
+```
+
+Or trigger `/swarm` right in chat:
+- `/swarm 5 workers using Gemini Argon to test src/`
+- `/swarm 5 workers using DeepSeek Flash to explore hypotheses`
+
 ## skills
 
 [`/poteto-mode`](./skills/poteto-mode/SKILL.md) runs most of these for you when a step needs them (`how`, `why`, `architect`, `arena`, `swarm`, `interrogate`, `unslop`, `no-comments`, `technical-writing`, `tdd`, and the principles). the table below is for when you want one directly:

diff --git a/rules/AGENTS.md b/rules/AGENTS.md
@@ -31,6 +31,10 @@ Mirroring pstack in Cursor, enforce strict separation between coordination and c
    - **Interactive State-Changing Playbooks (`Feature`, `Refactoring`, `Multi-phase`):** Mandatory `implementation_plan.md` with `RequestFeedback: true` before coding; mandatory `walkthrough.md` with pass receipts upon completion.
    - **Autonomous & Hillclimb Playbooks (`Autonomous run`, `Hillclimb`, `Swarm`, `/goal`, `/loop`):** Unattended throughput invariant. Use `RequestFeedback: false`. Domain deliverables (`decision_trail.md`, `score.json`, `receipts/`) take precedence without interactive blocking.
    - **Read-Only Investigation Playbooks (`Investigation`, `How`, `Why`, `Runtime Forensics`):** Produces `investigation_report.md` with `RequestFeedback: false`.
+6. **Cloud Swarm Model Selection & Zero-Friction Fallback:**
+   - **Prefer Tier 1 Serverless Models:** Default to frictionless serverless models that require zero console forms: `gemini-3.8-flash`, `gemini-4-argon`, or `deepseek-v4.1-flash` (MaaS).
+   - **Gated Partner Gating Detection:** If a user requests an Anthropic partner model (`claude-3-opus`, `claude-3-5-sonnet`) that is not yet enabled in Vertex AI Model Garden, explain that Google enforces a one-time console form click-through that agents cannot accept programmatically, and immediately offer the Tier 1 zero-friction alternative.
+   - **Open-Weights vs. MaaS Distinction:** Models like `GLM 5.3` or `Llama 3.3` on Model Garden are deployable open-weights requiring dedicated GPU endpoints (8x H100/B200 instances), not on-demand serverless APIs. Never attempt to dispatch Cloud Run tasks against deploy-only models without an active dedicated endpoint.
 
 ## Surface Precedence Hierarchy
 

diff --git a/skills/setup-agystack/SKILL.md b/skills/setup-agystack/SKILL.md
@@ -54,12 +54,19 @@ Do not leave the user to do the work. Complete the deployment end-to-end for the
 
 ### 2. Detect available models
 
-Enumerate the model tiers you can pass to `invoke_subagent`:
+Enumerate the model tiers you can pass to `invoke_subagent` (local) and `cloud_dispatch.py` (Cloud Run):
+
+**Local subagent tiers (`invoke_subagent`):**
 - `pro`: High-capability tier (maximum reasoning budget for complex code, architecture, and hard tasks)
 - `flash`: Balanced fast tier (fast execution for exploration and standard generation)
 - `flash_lite`: Lightweight tier (minimal latency for quick lookups)
 - `inherit` (or `auto`): Inherit parent chat model
 
+**Cloud Run swarm model tiers (`cloud_dispatch.py`):**
+- **Tier 1 (Zero-Friction MaaS):** `gemini-4-argon`, `gemini-3.8-flash`, `deepseek-v4.1-flash` (Instant on global Vertex endpoint, zero forms).
+- **Tier 2 (Gated Partner MaaS):** `claude-3-7-sonnet`, `claude-3-5-sonnet`, `claude-3-opus` (Requires one-time Console agreement).
+- **Tier 3 (Dedicated GPU Endpoint):** Open-weights models like `glm-5-3-flash` requiring dedicated 8x H100/B200 GPU instances.
+
 ### 3. Load current state
 
 If `~/.gemini/config/plugins/agystack/rules/agystack-models.md` exists, read its current role assignments. Otherwise start from skill defaults.

diff --git a/skills/setup-agystack/scripts/setup_runtime.py b/skills/setup-agystack/scripts/setup_runtime.py
@@ -115,6 +115,12 @@ def check_model_garden(project_id=None, region="us-central1", run_cmd_fn=None, i
         "project_id": project,
         "region": region,
         "anthropic_installed": False,
+        "serverless_models": [
+            "gemini-4-argon",
+            "gemini-3.8-flash",
+            "gemini-3.1-pro",
+            "deepseek-v4.1-flash-maas",
+        ],
         "partner_models": [
             "claude-3-7-sonnet@20250219",
             "claude-3-5-sonnet-v2@20241022",
@@ -140,9 +146,8 @@ def check_model_garden(project_id=None, region="us-central1", run_cmd_fn=None, i
                 result["error"] = f"Failed to initialize AnthropicVertex client: {init_exc}"
                 return result
     except ImportError:
-        result["ok"] = False
-        result["error"] = "Package 'anthropic[vertex]' is not installed (run: pip install anthropic[vertex])"
-        return result
+        result["anthropic_installed"] = False
+        result["partner_models_note"] = "Optional package 'anthropic[vertex]' not installed for Claude partner models."
     except Exception as exc:
         result["ok"] = False
         result["error"] = f"Error importing 'anthropic': {exc}"
@@ -576,6 +581,17 @@ def create_project(project_id):
     run_cmd(["gcloud", "projects", "create", project_id])
     print("Setting active project...")
     run_cmd(["gcloud", "config", "set", "project", project_id])
+    try:
+        res = run_cmd(["gcloud", "billing", "accounts", "list", "--format=json"], check=False)
+        if getattr(res, "returncode", 1) == 0:
+            accounts = json.loads(getattr(res, "stdout", "[]"))
+            open_accounts = [a for a in accounts if a.get("open", False)]
+            if open_accounts:
+                billing_id = open_accounts[0].get("name", "").split("/")[-1]
+                print(f"Linking billing account {billing_id} to project {project_id}...")
+                run_cmd(["gcloud", "billing", "projects", "link", project_id, f"--billing-account={billing_id}"], check=False)
+    except Exception:
+        pass
 
 def enable_apis(project_id):
     print(f"Enabling APIs for {project_id}...")
@@ -711,7 +727,7 @@ def _ignore_copy(directory, contents):
                             ignored.add(item)
                             continue
                         resolved_item = (dir_p / item).resolve()
-                        if resolved_item == dst_resolved or resolved_item == scripts_path:
+                        if resolved_item == dst_resolved or resolved_item == scripts_path or scripts_path in resolved_item.parents or resolved_item in scripts_path.parents:
                             ignored.add(item)
                     return ignored
 
@@ -723,7 +739,8 @@ def _ignore_copy(directory, contents):
             "gcloud", "builds", "submit",
             f"--tag={image_tag}",
             scripts_dir,
-            f"--project={project_id}"
+            f"--project={project_id}",
+            f"--region={region}"
         ], capture_output=False)
     finally:
         for staged in staged_dirs:

diff --git a/skills/swarm/SKILL.md b/skills/swarm/SKILL.md
@@ -42,6 +42,16 @@ Spawn all N workers in one `invoke_subagent` call with `TypeName: "poteto-agent"
 
 Cloud Run swarms enable parallel execution across dozens or hundreds of container tasks.
 
+**Model Selection & Friction Tiers:**
+
+Before launching cloud swarms, match the model to the project's Model Garden enablement status:
+
+| Tier | Models | Endpoint Type | Friction | Setup Required |
+|---|---|---|---|---|
+| **Tier 1: Native MaaS** | `gemini-4-argon`, `gemini-3.8-flash`, `deepseek-v4.1-flash` | Global Serverless | **Zero** | Instant via existing ADC / project IAM |
+| **Tier 2: Gated Partner MaaS** | `claude-3-7-sonnet`, `claude-3-5-sonnet`, `claude-3-opus` | Regional Serverless | **Low / One-Time** | Console agreement click-through required |
+| **Tier 3: Dedicated GPU** | `glm-5-3-flash`, `llama-3.3-70b` | Dedicated Endpoint | **High** | Dedicated 8x H100/B200 GPU instance provisioning |
+
 **Quota & Auth Prerequisites:**
 - **Paid Tier API Key or Vertex AI:** Cloud Run swarms require either a paid Google AI Studio tier (Pay-as-you-go / Tier 1+) or verified Vertex AI permissions (`roles/aiplatform.user` on the target project). Free-tier API keys (5 RPM) are prohibited as parallel container workers will immediately exhaust quota and fail.
 - **Git Authentication:** A valid GitHub token (`gh auth token` or `GH_TOKEN` / `GITHUB_TOKEN`) with repository clone access. Under the zero-push architecture, cloud containers do not require git push access.