OrgForge: A Multi-Agent Simulation Framework for Verifiable Synthetic Corporate Corpora

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.