feat(producer): thread variables through plan() + renderChunk() (#962)

Add `variables?: Record<string, unknown>` to DistributedRenderConfig
(§4.4) and LockedRenderConfig (§4.3). plan() snapshots the value into
meta/encoder.json so every chunk worker re-injects the same set via
captureOptions.variables, mirroring the in-process renderer's path.

The variables fold into planHash automatically because canonical
encoder.json bytes feed the hash: two plans with different variables
produce different hashes (chunked output depends on the injected
values); two plans with the same variables produce identical hashes
because canonical-JSON sorts keys.

The regression harnesses (distributed-simulated, lambda-local) also
forward the input's variables to plan() / Step Functions event so
fixtures that declare `renderConfig.variables` produce the same pixels
across modes. Previously the field was on the harness input shape but
silently dropped at the call boundary.

Phase 9 PR 9.1 of the distributed rendering plan.

packages/producer/src/regression-harness-lambda-local.ts

@@ -92,6 +92,11 @@ export async function runLambdaLocalRender(input: RunLambdaLocalInput): Promise<
     chunkSize: input.chunkSize,
     maxParallelChunks: input.maxParallelChunks,
     hdrMode: "force-sdr",
+    // Forward `variables` through the event boundary so lambda-local mode
+    // exercises the same variables-in-encoder.json path that real Lambda
+    // executions take. Without this, a fixture's `renderConfig.variables`
+    // would be silently dropped at the harness's serializer.
+    variables: input.variables,
   };
 
   // STEP A: plan