refactor(heartbeat): migrate heartbeat service to cron-based auto-registration

Remove standalone nanobot/heartbeat/ service and replace it with an
auto-registered system cron job on gateway startup. Key behaviors preserved:

- HeartbeatConfig (enabled, interval_s, keep_recent_messages) remains in
  GatewayConfig for backward compatibility.
- On startup, if enabled, a system cron job "heartbeat" is registered with
  schedule derived from interval_s.
- HEARTBEAT.md is checked on each tick; empty/template-identical files skip
  to avoid wasting LLM calls.
- Post-run evaluate_response and session history truncation
  (keep_recent_messages) are retained.
- Delivery target selection, deliverable filtering, and preamble guidance
  are preserved.

Files removed:
- nanobot/heartbeat/__init__.py
- nanobot/heartbeat/service.py
- tests/heartbeat/*
- tests/agent/test_heartbeat_service.py

Templates and docs updated to reflect cron-based usage.

.agent/gotchas.md

@@ -31,10 +31,6 @@ Tool descriptions, skills, and replayed session history also shape model behavio
 
 Anything written into memory, session history, or prompt inputs can be replayed into future LLM calls. Metadata such as timestamps, local media paths, tool-call echoes, and raw fallback dumps must be bounded and sanitized before they become examples for the model to imitate.
 
-## Heartbeat Virtual Tool Call
-
-The heartbeat service (`heartbeat/service.py`) does not parse free-text LLM output. Instead, it injects a virtual `heartbeat` tool with `action: skip | run` into the conversation. Phase 1 is a structured decision; Phase 2 executes only on `run`. When adding new periodic background checks, follow this virtual-tool-call pattern rather than string matching.
-
 ## Skills as Extension Point
 
 Built-in skills live in `nanobot/skills/` (markdown + YAML frontmatter format). Agent capabilities that are "know-how" rather than code should be added as skills, not hardcoded into the agent loop. External skills can be published to and installed from ClawHub.