Thư mục này quản lý cấu trúc kỹ thuật, lộ trình, quy tắc, và tóm tắt cấp cao của Dự án Nghiên cứu Chính sách Du lịch Việt Nam (đối sánh 5 nước Đông Nam Á).
Dự án nghiên cứu được quản lý tập trung qua 3 tài liệu chính:
/Users/keira/Documents/Obsidian Vault Mac/20_Areas/Public_Policy/Tourism_Research.sprint_2_2_report.md) được lưu trữ tại đây và đồng bộ tự động.Để tự động cập nhật danh mục tài liệu tham khảo (sources) theo chuẩn APA 7th và đồng bộ dữ liệu sang Git (docs/policy-research/), hãy chạy lệnh:
python3 Projects/vietnam-tourism-policy-research/scripts/sync_sources.py
This directory contains standard, executable step-by-step procedures (Workflows) designed to orchestrate agent operations across your projects. Workflows enforce systematic research, data integrity, and strict system maintenance.
| Slash Command / ID | Target Workflow File | Primary Purpose & Usage | Expected Output |
|---|---|---|---|
/research-general |
research-wf.md | Foundational General Research: Querying academic, expert, and community sources for diverse domains (health, travel, diet, etc.). Aliased as /research. |
Structured study saved to docs/research/ |
/research-policy-vn |
research-policy-vn-wf.md | Vietnam Policy Research: Quantitative and sequential multi-agent research into VN's tourism and inbound policies. | Policy Brief report saved to Obsidian Vault Mac/20_Areas/Public_Policy/Tourism_Research/ |
/atomic-complexity |
atomic-complexity-wf.md | Modular Decomposition: Auto-splitting complex rules, skills, or tasks exceeding cognitive thresholds into smaller modules. | Structured modularized plan and split files |
The following specialized agents are defined for orchestrating the Vietnam Tourism Policy Research workspace:
| Agent Identifier / Name | Role Title | Primary Specialty | Target Skills |
|---|---|---|---|
reporting_agent |
Master Policy Conductor | Overseeing the multi-agent flow, interacting with the user, and writing the final master briefs. | grill-me-alignment, ubiquitous-language |
problem_structuring_agent |
Problem Analyst Agent | Structuring policy issues, boundary analysis, identifying systemic failures (market vs. state). | boundary-analysis |
lit_review_agent |
Finder Agent | Coordinating literature search sub-agents (gov_specialist, media_specialist, social_specialist). |
ecosystem-causal-mapping, literature-search-archive |
detail_extractor_agent |
RAG Knowledge Retriever | Running NotebookLM queries via nlm CLI to retrieve qualitative/quantitative evidence. |
nlm-skill |
quantitative_data_agent |
Data Agent | Collecting raw statistics, expenditure patterns, length of stay, and tourism growth indicators. | Quantitative data collection |
research_writer_agent |
Writer Agent | Synthesizing reviews, drafting alternatives, compiling trade-off matrices, CBA/CEA, and M&E. | policy-impact-analysis, backward-mapping |
supervisor_agent |
Reviewer Agent | Fact-checking, citation validation (APA 7th + URLs), and independent NotebookLM checking. | policy-impact-analysis, nlm-skill |
logic_auditor_agent |
Logical & Causal Auditor | Auditing causal logic and reasoning, detecting logical fallacies, and ensuring evidence-backed policy. | Logical and causal auditing |