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P1: Token budget tracking (llm/llama_backend.py) - Auto-count input/output tokens per LLM call - BudgetExceededError when over limit - OpenAI API uses real usage data, Ollama estimates P2: Guardrails (tools/executor.py) - Block dangerous commands (rm -rf, git push --force, drop database, etc.) - Protect sensitive files (.env, credentials.json, id_rsa) - Confine writes to project_root P3: Execution observability (core/execution_trace.py) - Structured trace per task (steps, timing, tokens, success) - Human-readable summary() output P4: Session continuity (memory/session_md.py) - Auto-save SESSION.md on exit (recent task summaries) - Auto-load on next startup into Gate memory_context - Based on Claude Code 4-Layer Memory + Augment "Session-End Spec Update" Also fixed: apply_patch method accidentally dropped during executor.py rewrite. 311 tests passing. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>