docs(tools): state the Python SDK declarations are static stubs

A TypedDict reads as a constructible class, so a model that writes
FooArgs(field=1) fails with NameError before dispatch: the run request
injects only the tools namespace and ToolCallError. Say so in
SDK_INSTRUCTIONS and require plain dict/list JSON arguments. The TS
flavor needs no counterpart -- interface is visibly a type and its
"runs type-stripped" clause already covers erasure.

packages/core/tools/src/py-types.ts

@@ -519,7 +519,7 @@ export function jsonSchemaToPy(schema: unknown): string {
 /** The fixed model-facing usage contract rendered above the declarations. */
 const SDK_INSTRUCTIONS = `## Writing code for run_code
 
-Pass \`run_code\` the body of an async Python function (top-level \`await\` and \`return\` both work). Inside the program:
+Pass \`run_code\` the body of an async Python function (top-level \`await\` and \`return\` both work). Everything declared below is a STATIC STUB describing shapes: the \`TypedDict\` classes are NOT bound at run time, so build arguments as plain \`dict\`/\`list\` JSON values — \`await tools.name({"field": 1})\`, never \`FooArgs(field=1)\`, which raises \`NameError\`. Inside the program:
 
 - Call tools as \`await tools.name(args)\` — subscript access for exotic, reserved, or underscore-leading names: \`await tools["my-tool"](args)\`. Every call resolves to the tool's typed canonical JSON value (each method's return type below). Tool arguments must be lossless JSON.
 - A FAILED tool call raises \`ToolCallError\`, whose \`toolName\` identifies the failed tool and whose message is human-readable — wrap in \`try/except\` to handle and continue.