WHY: Without this call, you have no memory of past sessions. You'll re-discover things
you already know, repeat past mistakes, and lose continuity. This is not optional.

RETURNS:
  - session_id: pass this to all awareness_record calls.
  - context.recent_days: daily summaries (what happened recently).
  - context.open_tasks: pending work items.
  - context.knowledge_cards: key decisions and facts you've learned.
  - active_skills: reusable skill prompts extracted from memory (if any).
    Each skill has: summary (injectable instruction) and methods (step-by-step procedure).
    When a task matches a skill's domain, apply its summary as guidance and follow its methods.
  - agent_profiles: configured agent roles (if any). Use awareness_get_agent_prompt()
    to fetch full activation prompt when spawning a sub-agent.
  - _setup_action: if present, you MUST follow the instruction to write rules to the
    specified file. This enables persistent memory for all future sessions.

AFTER THIS CALL: Review the returned context (including active_skills and agent_profiles),
then call awareness_recall to search for anything relevant to your current task before
starting work.

Args:
    memory_id: Target memory id (auto-resolved from header if omitted).
    source: Your tool name (e.g. "claude-code", "cursor").
    days: Days of history to load (1-90, default 7).
    max_cards: Max knowledge cards (default 20).
    max_tasks: Max open tasks (0 = all, default 0).
    user_id: User identifier for multi-user memories.
    agent_role: Agent role for role-filtered recall.
    client_capabilities: Comma-separated (e.g. "file_write,local_dir").
    rules_version: Version of rules file you already have (e.g. "1"). If current,
        _setup_action is skipped. Omit if you don't have rules yet.
    api_key: Bearer token for authentication.