Use sandbox client for builder validation

agent.py

@@ -298,4 +298,4 @@ def _build_failure_error(exc: BaseException) -> str:
             "or a smaller build scope"
         )
     return f"build graph failed: {type(exc).__name__}: {exc}"
-# rebuild against a2a-pack 0.1.60 for source-grant-aware agent updates
+# rebuild against a2a-pack 0.1.75 for source-grant-aware agent updates

agent_builder/builder.py

@@ -321,6 +321,7 @@ def build_agent_builder(ctx: BuilderContext) -> Any:
             settings=settings,
             cp_jwt=ctx.cp_jwt,
             workspace=ctx.workspace,
+            sandbox=ctx.sandbox,
             grant_token=ctx.grant_token,
         )
     )

agent_builder/skills/a2apack-agent-authoring/SKILL.md

@@ -29,7 +29,7 @@ Reserve `LLMProvisioning.PLATFORM_OR_CALLER_PROVIDED` for legacy compatibility.
 In every mode, read `ctx.llm`;
 never read `A2A_LITELLM_KEY`, `OPENAI_API_KEY`, provider keys, or platform
 secrets directly. If `ctx.llm.api_key` is empty, return a clear setup/config
-result before constructing `ChatOpenAI`.
+result before constructing a model or calling `create_a2a_deep_agent`.
 
 `Pricing` only accepts `price_per_call_usd`, `caller_pays_llm`, and `notes`.
 Do not put `runtime.pricing.compute`, `runtime.pricing.total_usd`, `compute=`,

agent_builder/skills/agent-quality-review/SKILL.md

@@ -41,8 +41,8 @@ Check these items:
 - `Pricing` contains only `price_per_call_usd`, `caller_pays_llm`, and `notes`.
   Reject `runtime.pricing.compute`, `runtime.pricing.total_usd`, `compute=`, or
   `total_usd=` in `agent.py`; those are derived platform fields.
-- Any code path that builds `ChatOpenAI` checks `ctx.llm.api_key` first or
-  returns a clear setup/config result before the model constructor runs.
+- DeepAgents code uses `create_a2a_deep_agent` or another `ctx.llm`-backed
+  resolver, and checks `ctx.llm.api_key` before model construction.
 - Any use of DeepAgents file tools passes `backend=ctx.workspace_backend()`.
 - Any project skills are seeded into the backend and passed with
   `skills=skill_sources or None`.

agent_builder/skills/deepagent-agent-design/SKILL.md

@@ -1,6 +1,6 @@
 ---
 name: deepagent-agent-design
-description: Design generated A2A agents around DeepAgents skills, subagents, durable workspace backends, and ctx.llm-backed reasoning. Use whenever building or modifying an agent, deciding whether to add tools, creating skill bundles, wiring create_deep_agent, or avoiding shallow fake tools.
+description: Design generated A2A agents around DeepAgents skills, subagents, durable workspace backends, and ctx.llm-backed reasoning. Use whenever building or modifying an agent, deciding whether to add tools, creating skill bundles, wiring create_a2a_deep_agent, or avoiding shallow fake tools.
 ---
 # DeepAgent Agent Design
 
@@ -13,8 +13,8 @@ planning, file work, skill selection, and subagent delegation.
 Use this shape for non-trivial generated agents:
 
 1. Keep one or two public A2A `@skill` methods with clear typed parameters.
-2. Inside each method, read `ctx.llm`, verify credentials are available before
-   constructing `ChatOpenAI`, and build a DeepAgent with `create_deep_agent`.
+2. Inside each method, read `ctx.llm`, verify credentials are available, and
+   build a DeepAgent with `create_a2a_deep_agent`.
 3. Pass `backend=ctx.workspace_backend()` so DeepAgents file tools write to the
    caller's durable workspace instead of LangGraph state.
 4. Seed project skills into the current grant's write prefix and pass
@@ -44,7 +44,7 @@ linked from `SKILL.md`.
 
 Project `skills/` files are source files in the agent image. DeepAgents loads
 skills from its backend, so seed those files into the invocation workspace
-before `create_deep_agent`:
+before `create_a2a_deep_agent`:
 
 ```python
 from pathlib import Path
@@ -84,8 +84,9 @@ Then:
 ```python
 backend = ctx.workspace_backend()
 skill_sources = _seed_runtime_skills(backend, ctx)
-return create_deep_agent(
-    model=model,
+return create_a2a_deep_agent(
+    ctx,
+    creds=creds,
     backend=backend,
     skills=skill_sources or None,
     tools=[small_deterministic_tool],

agent_builder/skills/deepagents-implementation-patterns/SKILL.md

@@ -1,12 +1,12 @@
 ---
 name: deepagents-implementation-patterns
-description: Implement DeepAgents inside a2a-pack agents with real deterministic tools, project skills, custom subagents, workspace-backed files, and ctx.llm-backed ChatOpenAI models. Use when editing create_deep_agent calls or deciding what belongs in tools, skills, or subagents.
+description: Implement DeepAgents inside a2a-pack agents with real deterministic tools, project skills, custom subagents, workspace-backed files, and ctx.llm-backed model resolution. Use when editing create_a2a_deep_agent calls or deciding what belongs in tools, skills, or subagents.
 ---
 # DeepAgents Implementation Patterns
 
 DeepAgents supplies the inner agent loop. In this platform, the reliable shape
-is: `ctx.llm`-backed `ChatOpenAI`, A2A workspace backend, project DeepAgents
-skills, and a small number of exact tools. Hosted generated agents should
+is: `ctx.llm`-backed `create_a2a_deep_agent`, A2A workspace backend, project
+DeepAgents skills, and a small number of exact tools. Hosted generated agents should
 declare `LLMProvisioning.PLATFORM`; explicit BYOK agents can declare
 `CALLER_PROVIDED`, but both modes still read the same `ctx.llm` object.
 
@@ -20,8 +20,7 @@ from pathlib import Path
 from typing import Any
 
 from langchain_core.tools import tool
-from langchain_openai import ChatOpenAI
-from deepagents import create_deep_agent
+from a2a_pack.deepagents import create_a2a_deep_agent
 
 RUNTIME_SKILLS_DIR = "research-agent/.deepagents/skills/"
 
@@ -39,13 +38,6 @@ def build_graph(ctx: Any) -> Any:
             "LLM credentials were not available; declare PLATFORM for hosted "
             "generated agents or configure caller-provided credentials."
         )
-    model = ChatOpenAI(
-        model=creds.model,
-        base_url=creds.base_url,
-        api_key=creds.api_key,
-        temperature=0.0,
-    )
-
     @tool
     def validate_citations(items_json: str) -> str:
         """Validate that each citation has title, url, and claim fields."""
@@ -58,8 +50,9 @@ def build_graph(ctx: Any) -> Any:
 
     backend = ctx.workspace_backend()
     skill_sources = seed_runtime_skills(backend, ctx)
-    return create_deep_agent(
-        model=model,
+    return create_a2a_deep_agent(
+        ctx,
+        creds=creds,
         backend=backend,
         skills=skill_sources or None,
         tools=[validate_citations],

agent_builder/skills/workspace-artifact-safety/SKILL.md

@@ -26,7 +26,7 @@ Pass the backend into DeepAgents:
 
 ```python
 backend = ctx.workspace_backend()
-graph = create_deep_agent(model=model, backend=backend, skills=skill_sources or None)
+graph = create_a2a_deep_agent(ctx, backend=backend, skills=skill_sources or None)
 ```
 
 For stable, human-readable paths, ask model-created files to use

agent_builder/tools.py

@@ -31,7 +31,7 @@ if TYPE_CHECKING:
     from .config import Settings
 
 
-A2A_PACK_MIN_VERSION = "0.1.60"
+A2A_PACK_MIN_VERSION = "0.1.75"
 
 
 @dataclass(frozen=True)
@@ -40,6 +40,7 @@ class ToolContext:
     settings: "Settings"
     cp_jwt: str | None = None
     workspace: Any | None = None
+    sandbox: Any | None = None
     grant_token: str | None = None
 
 
@@ -444,6 +445,29 @@ def build_tools(ctx: ToolContext) -> list[Any]:
             "  a2a frontend info --project . || true\n"
             "fi\n"
         )
+        if ctx.sandbox is not None:
+            try:
+                out = await ctx.sandbox.run_shell(
+                    script,
+                    image=settings.image,
+                    workspace=bucket,
+                    memory_mib=512,
+                    timeout_seconds=settings.sandbox_timeout_s,
+                )
+            except Exception as exc:  # noqa: BLE001
+                return json.dumps({
+                    "error": f"sandbox {type(exc).__name__}",
+                    "detail": str(exc)[:1000],
+                })
+            result: dict[str, Any] = {
+                "exit_code": getattr(out, "exit_code", None),
+                "stdout": (getattr(out, "stdout", "") or "")[:4000],
+                "stderr": (getattr(out, "stderr", "") or "")[:4000],
+            }
+            if sanitized_fields:
+                result["sanitized_agent_card_fields"] = list(sanitized_fields)
+            return json.dumps(result)
+
         headers = _sandbox_headers(settings.sandbox_token, ctx.grant_token)
         async with httpx.AsyncClient(timeout=settings.sandbox_timeout_s + 30) as c:
             r = await c.post(

requirements.txt

@@ -1,4 +1,4 @@
-a2a-pack>=0.1.60
+a2a-pack>=0.1.75
 httpx>=0.27
 boto3>=1.34
 deepagents>=0.5.0

tests/test_builder_prompt.py

@@ -162,7 +162,7 @@ inline = Pricing(price_per_call_usd=0.01, compute={"runtime_seconds": 600}, tota
         self.assertIn("skills=skill_sources or None", files["deepagent-agent-design/SKILL.md"])
         self.assertIn("from a2a_pack import", files["a2apack-agent-authoring/SKILL.md"])
         self.assertIn("ctx.workspace_shell", files["a2apack-agent-authoring/SKILL.md"])
-        self.assertIn("create_deep_agent", files["deepagents-implementation-patterns/SKILL.md"])
+        self.assertIn("create_a2a_deep_agent", files["deepagents-implementation-patterns/SKILL.md"])
         self.assertIn('config={"recursion_limit": 500}', files["deepagents-implementation-patterns/SKILL.md"])
         self.assertIn("ctx.write_artifact", files["workspace-artifact-safety/SKILL.md"])
         self.assertIn("ctx.workspace_shell", files["workspace-artifact-safety/SKILL.md"])

tests/test_template_init.py

@@ -47,7 +47,7 @@ class TemplateInitTests(unittest.TestCase):
         self.assertIn("skills=skill_sources or None", files["agent.py"])
         self.assertIn("ctx.llm", files["agent.py"])
         self.assertIn("ctx.workspace_backend()", files["agent.py"])
-        self.assertIn("create_deep_agent", files["agent.py"])
+        self.assertIn("create_a2a_deep_agent", files["agent.py"])
         self.assertIn("name: research-agent", files["a2a.yaml"])
         self.assertIn("entrypoint: agent:ResearchAgent", files["a2a.yaml"])
         self.assertNotIn("{{ frontend_block }}", files["a2a.yaml"])
@@ -272,6 +272,35 @@ class TemplateInitTests(unittest.TestCase):
 
         self.assertIn("manifest_json must be a JSON object", result["error"])
 
+    def test_test_agent_in_sandbox_uses_attached_sandbox_client(self) -> None:
+        workspace = _FakeWorkspace()
+        prefix = "agents/demo-agent/"
+        workspace.write_bytes(prefix + "agent.py", b"print('ok')\n")
+        workspace.write_bytes(prefix + "a2a.yaml", b"name: demo-agent\n")
+        workspace.write_bytes(prefix + "requirements.txt", b"")
+        sandbox = _FakeSandbox()
+        tools = build_tools(
+            ToolContext(
+                bucket="bucket",
+                settings=_settings(),
+                workspace=workspace,
+                sandbox=sandbox,
+                grant_token="grant-token",
+            )
+        )
+        test_tool = _tool_by_name(tools, "test_agent_in_sandbox")
+
+        _FakeAsyncClient.posts = []
+        with patch("agent_builder.tools.httpx.AsyncClient", _FakeAsyncClient):
+            result = json.loads(
+                asyncio.run(test_tool.ainvoke({"name": "demo-agent"}))
+            )
+
+        self.assertEqual(result["exit_code"], 0)
+        self.assertEqual(len(sandbox.calls), 1)
+        self.assertEqual(sandbox.calls[0]["workspace"], "bucket")
+        self.assertEqual(_FakeAsyncClient.posts, [])
+
     def test_cp_deploy_tarball_posts_agent_dsl(self) -> None:
         workspace = _FakeWorkspace()
         prefix = "agents/demo-agent/"
@@ -529,6 +558,21 @@ class _FakeWorkspace:
         self.objects.pop(key, None)
 
 
+class _FakeExecResult:
+    exit_code = 0
+    stdout = "--- card ---\n{}"
+    stderr = ""
+
+
+class _FakeSandbox:
+    def __init__(self) -> None:
+        self.calls: list[dict[str, object]] = []
+
+    async def run_shell(self, script: str, **kwargs: object) -> _FakeExecResult:
+        self.calls.append({"script": script, **kwargs})
+        return _FakeExecResult()
+
+
 def _tool_by_name(tools: list[object], name: str) -> object:
     for tool in tools:
         if getattr(tool, "name", None) == name: