A professional automation skill for designing refreshable Excel dashboards using Power Query, structured tables, and automated data validation.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install excel-weekly-dashboard
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install excel-weekly-dashboard using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Excel Weekly Dashboard Skill?
The Excel Weekly Dashboard skill is designed to architect and build repeatable reporting pipelines within Microsoft Excel. By utilizing Openclaw Skills, this agent creates robust Power Query workflows that ingest data from folders, CSVs, or XLSX files, transforming raw data into clean, pivot-ready tables. It prioritizes a "no-manual-work" philosophy, ensuring that your reporting remains stable even as weekly data accumulates or source columns shift.
This skill goes beyond simple spreadsheet creation by implementing developer-grade data integrity practices. It establishes a clear separation between raw ingestion and cleaned data, incorporating validation flags and refresh health checks. When using Openclaw Skills for your reporting needs, you gain a scalable framework that handles data normalization, type safety, and professional visualization layouts without the fragility typical of manual Excel models.
Excel Weekly Dashboard Skill Use Cases
- Automating weekly KPI updates from a folder of CSV exports to eliminate manual copy-pasting.
- Converting unstructured data dumps into clean tables with strict data entry and validation rules.
- Building interactive dashboards with slicers for ISO weeks and operational dimensions.
- Refactoring fragile Excel models that break when source files change column order or naming.
- Creating a centralized reporting hub that aggregates data from multiple exported PDF or Word tables.
How Excel Weekly Dashboard Skill Works
- The skill identifies source file types and locates stable business keys to ensure data continuity.
- It defines a canonical table schema specifying required columns, data types, and handling rules for missing values.
- A Power Query ingestion layer is designed, preferably using folder-ingest methods with defensive column logic.
- It creates a dual-stage query system: a staging layer for raw normalization and a clean layer for validated data.
- A reporting layer is constructed using pivot tables and interactive slicers driven by the clean data query.
- A refresh status dashboard is integrated to provide visibility into row counts, timestamps, and potential errors.
Excel Weekly Dashboard Skill Setup
To deploy this dashboard logic within your Openclaw Skills workflow, provide the agent with your source file samples and KPI requirements.
# Typical interaction to start the build plan
openclaw run excel-weekly-dashboard --files ./data/weekly_exports/
The skill will output a comprehensive workbook plan or specific artifacts like power_query_steps.pq and a workbook_spec.md to guide the manual or automated setup of the Excel environment.
Excel Weekly Dashboard Skill Data Schema & Taxonomy
The skill organizes Excel workbooks into a logical hierarchy to maintain data integrity and performance within Openclaw Skills implementations:
| Sheet Name | Role | Description |
|---|---|---|
| Data_Staging | Ingestion | The direct output of the raw data Power Query. |
| Data_Clean | Validation | Normalized data enriched with validation flags (e.g., IsValidDate). |
| Dashboard | Reporting | The user-facing layer containing pivots, charts, and slicers. |
| Refresh_Status | Monitoring | Logs for last refresh, row counts, and query health checks. |
Excel Weekly Dashboard Skill Advanced Features
- Defensive missing-column handling to prevent refresh crashes during schema drift.
- Automated normalization of column headers (trimming, casing, and space collapsing).
- Multi-query staging architectures that separate data cleaning from data ingestion.
- ISO week and year slicer integration for standardized chronological reporting.
- Refresh health monitoring with visible error flags for non-technical users.
SKILL.md
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