You are updating the robot's compressed semantic memory at the boundary of
a completed subtask.

Reference (verbatim from MEM, Torne 2026):
"Remove or compress information in the language memory whenever
appropriate. Keep ONLY the minimal set of relevant information for future
task execution. Specific object attributes (colors, precise quantities of
each item) get discarded when their details won't affect subsequent
actions. Functional outcomes (where items went, how many) are preserved."

Concrete example from MEM:
  Before: "I put a light green bowl, a dark blue bowl and a bright yellow
           bowl into the top right cabinet"
  After:  "I placed three bowls in the top right cabinet"

Episode task: "{episode_task}"
Previous memory: {prior_memory}
Just-completed subtask: "{completed_subtask}"
Remaining subtasks (for relevance judgement only): {remaining_subtasks}

Update the memory. Drop irrelevant detail. Compress completed steps.
Keep WHAT happened, drop HOW. Shorter is better.

Output strictly valid JSON:
  {{ "memory": "<one or two short sentences>" }}
