v1.2.5--arvix-preprint

Added

• Global Voice Card System (utils/persona_utils.py, src/normal_day.py): Migrated individual persona logic to a centralized get_voice_card utility. This provides context-aware character sheets (e.g., async, design, collision) that inject tenure, expertise, mood, and "anti-patterns" into LLM backstories to prevent generic corporate drift.
• Robust JSON Recovery (requirements.txt, src/flow.py, src/normal_day.py): Integrated json-repair across the simulation pipeline. This allows the engine to "salvage" malformed LLM responses in ticket generation and Slack conversations, significantly reducing "failed to parse" fallbacks.

Changed

• Persona History Filtering (src/memory.py): Enhanced persona_history to filter out "noisy" macro-events (like sprint planning summaries or standups). This ensures agents focus on personal agency and direct interactions when building their local context.
• Incident Recurrence Logic (src/causal_chain_handler.py): Refined the RecurrenceDetector to prioritize the earliest incident in a chain (anti-daisy-chaining). This ensures new incidents link back to the original root cause rather than just the most recent duplicate.
• Streamlined codebase (Across all files): Conducted a major cleanup of legacy comments, "ASCII art" section dividers, and redundant docstrings to improve readability and reduce token overhead during development.

Fixed

• PR Causal Linking (src/flow.py): Fixed a bug where PR IDs were missing from the persistent ticket record. PRs are now immediately appended to the CausalChainHandler and saved to MongoDB upon creation.
• Department Signal Noise (src/day_planner.py): Non-engineering departments (Sales, HR) now only receive "direct" relevance signals, preventing them from being overwhelmed by technical incident data that doesn't impact their planning.