Use sandbox client for builder validation

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(