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dashboard-view-builder
Building and managing premium statistical dashboards, RAG explorer UIs, warehouse log monitors, and real-time visualization centers.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
菜单
Building and managing premium statistical dashboards, RAG explorer UIs, warehouse log monitors, and real-time visualization centers.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Automated governance, hook installation, pre-commit validation, branch isolation, and safe commit operations.
Enforcement of safety guardrails, axiom verification, secret scanning, and mutability protections.
Integration of agent systems with blockchain protocols, contracts, event stores, reputation networks, and collective verification engines.
AI model configuration, LLM memoization, agentic RAG search, and vector library maintenance.
Catalog generation, reference link verification, workshop documentation building, and knowledge gap analysis.
Master system orchestration, blueprint rendering, project scaffolding, multi-agent debates, and SDLC stage validators.
| name | dashboard-view-builder |
| description | Building and managing premium statistical dashboards, RAG explorer UIs, warehouse log monitors, and real-time visualization centers. |
| type | skill |
| version | 1.0.0 |
| category | parallel |
| agents | ["full-stack-web-specialist","master-system-orchestrator"] |
| knowledge | ["ui-design-patterns.json"] |
| scripts | ["projects/rag_knowledge_explorer/app.py","projects/rag_knowledge_explorer/core/ai_manager.py","projects/rag_knowledge_explorer/core/config_manager.py","projects/rag_knowledge_explorer/core/rag_manager.py","projects/statistical_dashboards/_pages/warehouse_inbound.py","projects/statistical_dashboards/_pages/warehouse_inventory.py","projects/statistical_dashboards/_pages/warehouse_outbound.py","projects/statistical_dashboards/app.py","projects/statistical_dashboards/core/ai_manager.py","projects/statistical_dashboards/core/analysis_manager.py","projects/statistical_dashboards/core/business_manager.py","projects/statistical_dashboards/core/config_manager.py","projects/statistical_dashboards/core/connectors/economic_connector.py","projects/statistical_dashboards/core/connectors/financial_connector.py","projects/statistical_dashboards/core/connectors/news_connector.py","projects/statistical_dashboards/core/data_manager.py","projects/statistical_dashboards/core/database.py","projects/statistical_dashboards/core/guidance_center.py","projects/statistical_dashboards/core/memory_sync.py","projects/statistical_dashboards/core/report_manager.py","projects/statistical_dashboards/core/templates.py","projects/statistical_dashboards/core/tools.py","projects/statistical_dashboards/core/validation_manager.py","projects/statistical_dashboards/core/viz_manager.py","projects/statistical_dashboards/core/workflows.py","projects/statistical_dashboards/data_generator.py","projects/statistical_dashboards/scripts/data_guard.py","projects/statistical_dashboards/scripts/kpi_publisher.py","projects/statistical_dashboards/scripts/kpi_scanner.py","projects/statistical_dashboards/scripts/report_generator.py","projects/statistical_dashboards/scripts/sync_tasks_to_db.py"] |
| tools | [] |
| related_skills | ["building-nextjs"] |
| references | [] |
| settings | {"auto_approve":false,"timeout_seconds":300} |
This skill enables the development, hosting, and data management of interactive dashboards (Streamlit/Next.js), RAG explorer centers, database connectors, and warehouse tracking tools.
Use this skill when modifying statistical dashboards, writing custom connectors (news, financial, economic), implementing data guards, or deploying interactive knowledge explorers.
Follow these procedures to build and launch interactive dashboards.
Start the statistical warehouse dashboard or RAG knowledge explorer locally:
conda run -p D:\Anaconda\envs\cursor-factory streamlit run projects/statistical_dashboards/app.py
conda run -p D:\Anaconda\envs\cursor-factory streamlit run projects/rag_knowledge_explorer/app.py
Scan incoming metrics for outliers or schema anomalies:
conda run -p D:\Anaconda\envs\cursor-factory python projects/statistical_dashboards/scripts/data_guard.py