Require user LLM credentials

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

@@ -1,6 +1,6 @@
 ---
 name: a2apack-agent-authoring
-description: Author production a2a-pack agents with clear public @skill schemas, runtime declarations, platform LLM grants, optional caller-provided LLMs, workspace grants, pricing, resources, and secure platform capabilities. Use when writing or reviewing agent.py for an A2A agent.
+description: Author production a2a-pack agents with clear public @skill schemas, runtime declarations, caller-funded LLM credentials, optional agent BYOK, workspace grants, pricing, resources, and secure platform capabilities. Use when writing or reviewing agent.py for an A2A agent.
 ---
 # A2A Pack Agent Authoring
 
@@ -22,12 +22,11 @@ Use `A2AAgent` class attributes for runtime and marketplace behavior:
   caller's control-plane token.
 
 For hosted generated/user-owned agents that call an LLM, default to
-`LLMProvisioning.PLATFORM` with `Pricing(..., caller_pays_llm=False, ...)` so
-main-agent handoffs mint a scoped A2A LiteLLM grant for the callee. Use
-`LLMProvisioning.CALLER_PROVIDED` only when the user explicitly wants BYOK or
-caller-paid inference. Reserve `LLMProvisioning.PLATFORM_OR_CALLER_PROVIDED`
-for trusted platform/meta agents that must work with either the caller's
-selected creds or a platform fallback grant. In every mode, read `ctx.llm`;
+`LLMProvisioning.PLATFORM` with `Pricing(..., caller_pays_llm=True, ...)` so
+main-agent handoffs forward the caller's saved LLM credential for the callee.
+`LLMProvisioning.CALLER_PROVIDED` is still acceptable for explicit BYOK wording.
+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`.
@@ -79,8 +78,8 @@ class ResearchAgent(A2AAgent[ResearchConfig, NoAuth]):
     llm_provisioning = LLMProvisioning.PLATFORM
     pricing = Pricing(
         price_per_call_usd=0.05,
-        caller_pays_llm=False,
-        notes="Uses a scoped platform LLM grant through ctx.llm.",
+        caller_pays_llm=True,
+        notes="Uses the caller's saved LLM credential through ctx.llm.",
     )
     resources = Resources(cpu="1", memory="1Gi", max_runtime_seconds=900)
     egress = EgressPolicy(allow_hosts=("api.openai.com",))

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

@@ -35,10 +35,9 @@ Check these items:
   only for trusted platform/meta agents and must also read `ctx.llm`.
 - Hosted generated/user agents should default to
   `llm_provisioning = LLMProvisioning.PLATFORM` and
-  `Pricing(..., caller_pays_llm=False, ...)`. Use
-  `LLMProvisioning.CALLER_PROVIDED` only when the user explicitly wants BYOK or
-  caller-paid inference. In both modes, the code must use `ctx.llm` and never
-  read LiteLLM/provider keys directly.
+  `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.
 - `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.