feat(loop): add REASONIX anti-wandering loop guards

[raymondginger2018-sudo]

Summary

Adds anti-wandering loop guards to the agent runtime loop: an evidence ledger, a progress guard, a storm breaker, and delegation admission. When the model starts spinning (repeated tool calls producing no new evidence), the guards inject escalating interventions and can force a final answer instead of burning the remaining budget on the same failure pattern.

The engine lives in core/loop/guards.py (stdlib-only, zero internal dependencies) with an optional telemetry seam in core/loop/guard_telemetry.py (enabled via DEEPCODE_GUARD_TELEMETRY=1, zero overhead by default).

Wiring

• runner.py — blocked short-circuit before tool execution, observe_batch injection after each tool batch, per-tool check_tool governance gate, and success-path observation hooks.
• session.py — threads a LoopGuards instance through AgentSession → AgentRunSpec.
• spawn_agent.py — delegation admission gate (REASONIX delegationAdmission adaptation) so a sub-agent that references parent-context without inheriting it (fork_turns='none') is rejected with an actionable error.
• loop/__init__.py — public exports for the guard API.

Behavior notes

• Guards are opt-in: guards: LoopGuards | None = None on AgentRunSpec; absent means zero cost.
• Blocks are errors-as-data (never exceptions): the model reads the block reason as a tool result and wraps up cleanly.
• guard_event_callback receives structured events (blocked / injection / tool_block) for telemetry without changing default logging behavior.

Testing

• tests/test_guards.py — evidence ledger scoring, progress-guard escalation (2/4/6), storm-breaker circuit breaking, delegation admission.
• tests/test_guard_telemetry.py — telemetry wiring and event payloads.
• 37 new tests, all passing.

Origin

This is a Python port of the applyBatchGuards component family (evidence ledger, progress guard, storm breaker, delegation admission) from DeepSeek-Reasonix (MIT licensed), adapted to DeepCode's run-loop conventions. The implementation is a fresh Python rewrite following the original design semantics — not a code copy. Original project: esengine/DeepSeek-Reasonix (MIT License).