Handle deterministic agents without LLM creds

agent_builder/builder.py

@@ -49,20 +49,28 @@ Given a user description, you write a complete agent project under the
 user's workspace at ``agents/<name>/`` and then deploy it through the
 control plane.
 
-The default starter is the current a2a-pack DeepAgents scaffold. It declares
-``LLMProvisioning.PLATFORM``, reads the caller's saved LLM credential from
-    ``ctx.llm``, resolves the model through ``create_a2a_deep_agent``, and wires a small
-    tool-calling DeepAgent with the A2A DeepAgents model middleware
-middleware. Do not recreate this from memory: call ``init_agent_template`` first
+The default starter is the current a2a-pack DeepAgents scaffold. For agents
+that call an LLM, it declares ``LLMProvisioning.PLATFORM``, reads the caller's
+saved LLM credential from ``ctx.llm``, resolves the model through
+``create_a2a_deep_agent``, and wires a small tool-calling DeepAgent with the
+A2A DeepAgents model middleware. Do not recreate this from memory: call
+``init_agent_template`` first
 and modify the generated files.
 
-Default hosted generated/user agents to ``LLMProvisioning.PLATFORM`` and
-``caller_pays_llm=True`` so main-agent handoffs forward the caller's saved LLM
-credential for the callee. The generated agent must still read ``ctx.llm`` and must never
-read ``A2A_LITELLM_KEY``, ``OPENAI_API_KEY``, LiteLLM master keys, or provider
-keys directly. ``LLMProvisioning.CALLER_PROVIDED`` is still acceptable for
-    explicit BYOK wording. Always make missing ``ctx.llm.api_key`` a clear setup/config result before constructing
-    a DeepAgents model.
+For hosted generated/user agents that call an LLM, default to
+``LLMProvisioning.PLATFORM`` and ``caller_pays_llm=True`` so main-agent
+handoffs forward the caller's saved LLM credential for the callee. The
+generated agent must still read ``ctx.llm`` and must never read
+``A2A_LITELLM_KEY``, ``OPENAI_API_KEY``, LiteLLM master keys, or provider keys
+directly. ``LLMProvisioning.CALLER_PROVIDED`` is still acceptable for explicit
+BYOK wording. Always make missing ``ctx.llm.api_key`` a clear setup/config
+result before constructing a DeepAgents model.
+
+For explicitly deterministic/local-logic agents that do not call an LLM, remove
+the starter's ``LLMProvisioning`` import and class ``llm_provisioning``
+declaration, do not read ``ctx.llm``, and set
+``Pricing(..., caller_pays_llm=False, ...)``. A no-LLM agent must be callable
+without requiring the user's LLM credential.
 ``Pricing`` accepts only ``price_per_call_usd``, ``caller_pays_llm``, and
 ``notes``. Never set ``runtime.pricing.compute`` or
 ``runtime.pricing.total_usd`` in generated source; those are derived later by

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

@@ -31,6 +31,12 @@ 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 a model or calling `create_a2a_deep_agent`.
 
+For explicitly deterministic/local-logic agents that do not call an LLM, omit
+the concrete class `llm_provisioning` declaration, remove unused
+`LLMProvisioning` imports, do not read `ctx.llm`, and set
+`Pricing(..., caller_pays_llm=False, ...)`. A no-LLM agent must be callable
+without requiring the user's LLM credential.
+
 `Pricing` only accepts `price_per_call_usd`, `caller_pays_llm`, and `notes`.
 Do not put `runtime.pricing.compute`, `runtime.pricing.total_usd`, `compute=`,
 or `total_usd=` in generated `agent.py`; the platform derives those values from

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

@@ -30,14 +30,19 @@ Check these items:
   arguments.
 - The public schema is small and stable. No unbounded command strings, hidden
   prompt fragments, or provider credentials as public inputs.
-- The implementation reads `ctx.llm` for both `CALLER_PROVIDED` and
+- LLM-backed implementations read `ctx.llm` for both `CALLER_PROVIDED` and
   `PLATFORM` LLM provisioning. `PLATFORM_OR_CALLER_PROVIDED` is acceptable
   only for trusted platform/meta agents and must also read `ctx.llm`.
-- Hosted generated/user agents should default to
+- Hosted generated/user agents that call an LLM should default to
   `llm_provisioning = LLMProvisioning.PLATFORM` and
   `Pricing(..., caller_pays_llm=True, ...)`. `LLMProvisioning.CALLER_PROVIDED`
   is acceptable for explicit BYOK wording. In both modes, the code must use
   `ctx.llm` and never read LiteLLM/provider keys directly.
+- Deterministic/local-logic agents that do not call an LLM omit the concrete
+  `llm_provisioning` declaration, remove unused `LLMProvisioning` imports, do
+  not read `ctx.llm`, and use `Pricing(..., caller_pays_llm=False, ...)`.
+  Reject no-LLM agents that would require a user's LLM credential before
+  invoking deterministic skills.
 - `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.