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* fix(security): guard goes active; CEO A2A respects no-comms roles; ack notifications expire ROBOCO_GUARD_PASSIVE_MODE defaults to false in both compose files — the deferred post-calibration flip; fail_secure stays off and the env override remains the rollback. can_a2a_direct no longer short-circuits the CEO past the no-comms set (auditor/pr_reviewer/prompter/secretary), now canonical in foundation.policy.communications.NO_COMMS_ROLES and shared with the content-actions gate; the A2A service refuses at conversation creation instead of silently suppressing the wake. Ack-required notifications get expires_at stamped from ROBOCO_NOTIFICATION_ACK_TTL_HOURS (default 48, 0 disables), so the re-escalation sweeper's expires_at query matches rows for the first time. * refactor(notification): extract _ack_and_expiry — xenon rank back under B The expires_at stamping pushed _create_notification_with_session to rank C; the requires_ack + expiry derivation moves into a helper with the same semantics and comments. * test(conftest): dispose the global DB engine after every test Production code reaching get_db_context()/get_engine() lazily creates the process-global engine bound to the current event loop; with per-test function-scoped loops, any later test touching the global path inherits a dead-loop engine and dies with 'Future attached to a different loop' — the order-dependent class that has been wandering the suite (cloud_auth login, metrics, tasks-routes, full-lifecycle) whenever collection order shifts. An autouse fixture now close_db()s after every test, keeping the global path loop-local; no-op when untouched. --------- Co-authored-by: Renn F <rennf93@users.noreply.github.com>
RAG Knowledge Base Documentation
Optimized documentation for the RoboCo AI agent knowledge base. Each file is sized for effective RAG chunking.
Structure
docs/rag/
├── roles/ # Agent role responsibilities
├── workflows/ # Step-by-step task flows
├── standards/ # Coding, security, testing rules
├── architecture/ # System components
├── tools/ # MCP tools reference
└── troubleshooting/ # Common issues and fixes
Organization Principles
- One topic per file - Each file covers a single concept
- Chunk-friendly - Content fits in 512-1536 token chunks
- Self-contained - Each file provides complete context
- Actionable - Focus on what agents need to DO
For Agents
When searching the knowledge base:
- Use
roboco_kb_search()for semantic search - Use
roboco_rag_query()for AI-synthesized answers - Use
roboco_ask_mentor()for conversational help
See docs/rag/tools/kb-tools.md for the full KB tool reference.