excel-weekly-dashboard

تایید شده

Designs refreshable Excel dashboards (Power Query + structured tables + validation + pivot reporting). Use when you need a repeatable weekly KPI workbook that updates from files with minimal manual work.

@openclaw
MIT۱۴۰۴/۱۲/۳
65از ۱۰۰
(0)
۱.۰k
۳۹
۴۳

نصب مهارت

مهارت‌ها کدهای شخص ثالث از مخازن عمومی GitHub هستند. SkillHub الگوهای مخرب شناخته‌شده را اسکن می‌کند اما نمی‌تواند امنیت را تضمین کند. قبل از نصب، کد منبع را بررسی کنید.

نصب سراسری (سطح کاربر):

npx skillhub install openclaw/skills/excel-weekly-dashboard

نصب در پروژه فعلی:

npx skillhub install openclaw/skills/excel-weekly-dashboard --project

مسیر پیشنهادی: ~/.claude/skills/excel-weekly-dashboard/

بررسی هوش مصنوعی

کیفیت دستورالعمل65
دقت توضیحات75
کاربردی بودن57
صحت فنی65

Scored 65. Standout description with 5 triggers and 3 anti-triggers — rare in this review set. Power Query M template with defensive schema handling adds real technical value. Refresh checklist makes it operational. Deducted for Excel-only scope.

محتوای SKILL.md

---
name: excel-weekly-dashboard
description: Designs refreshable Excel dashboards (Power Query + structured tables + validation + pivot reporting). Use when you need a repeatable weekly KPI workbook that updates from files with minimal manual work.
---

# Excel weekly dashboards at scale

## PURPOSE
Designs refreshable Excel dashboards (Power Query + structured tables + validation + pivot reporting).

## WHEN TO USE
- TRIGGERS:
  - Build me a Power Query pipeline for this file so it refreshes weekly with no manual steps.
  - Turn this into a structured table with validation lists and clean data entry rules.
  - Create a pivot-driven weekly dashboard with slicers for year and ISO week.
  - Fix this Excel model so refresh does not break when new columns appear.
  - Design a reusable KPI pack that updates from a folder of CSVs.
- DO NOT USE WHEN…
  - You need advanced forecasting/valuation modeling (this skill is for repeatable reporting pipelines).
  - You need a BI tool build (Power BI/Tableau) rather than Excel.
  - You need web scraping as the primary ingestion method.

## INPUTS
- REQUIRED:
  - Source data file(s): CSV, XLSX, DOCX-exported tables, or PDF-exported tables (provided by user).
  - Definition of ‘week’ (ISO week preferred) and the KPI fields required.
- OPTIONAL:
  - Data dictionary / column definitions.
  - Known “bad data” patterns to validate (e.g., blank PayNumber, invalid dates).
  - Existing workbook to refactor.
- EXAMPLES:
  - Folder of weekly CSV exports: `exports/2026-W02/*.csv`
  - Single XLSX dump with changing columns month to month

## OUTPUTS
- If asked for **plan only (default)**: a step-by-step build plan + Power Query steps + sheet layout + validation rules.
- If explicitly asked to **generate artifacts**:
  - `workbook_spec.md` (workbook structure and named tables)
  - `power_query_steps.pq` (M code template)
  - `refresh-checklist.md` (from `assets/`)
Success = refresh works after adding a new week’s files without manual edits, and validation catches bad rows.


## WORKFLOW
1. Identify source type(s) (CSV/XLSX/DOCX/PDF-export) and the stable business keys (e.g., PayNumber).
2. Define the canonical table schema:
   - required columns, types, allowed values, and “unknown” handling.
3. Design ingestion with Power Query:
   - Prefer **Folder ingest** + combine, with defensive “missing column” handling.
   - Normalize column names (trim, case, collapse spaces).
4. Design cleansing & validation:
   - Create a **Data_Staging** query (raw-normalized) and **Data_Clean** query (validated).
   - Add validation columns (e.g., `IsValidPayNumber`, `IsValidDate`, `IssueReason`).
5. Build reporting layer:
   - Pivot table(s) off **Data_Clean**
   - Slicers: Year, ISOWeek; plus operational dimensions
6. Add a “Refresh Status” sheet:
   - last refresh timestamp, row counts, query error flags, latest week present
7. STOP AND ASK THE USER if:
   - required KPIs/columns are unspecified,
   - the source files don’t include any stable key,
   - week definition/timezone rules are unclear,
   - PDF/DOCX tables are not reliably extractable without a provided export.


## OUTPUT FORMAT
When producing a **plan**, use this template:

```text
WORKBOOK PLAN
- Sheets:
  - Data_Staging (query output)
  - Data_Clean (query output + validation flags)
  - Dashboard (pivots/charts)
  - Refresh_Status (counts + health checks)
- Canonical Schema:
  - <Column>: <Type> | Required? | Validation
- Power Query:
  - Query 1: Ingest_<name> (Folder/File)
  - Query 2: Clean_<name>
  - Key transforms: <bullets>
- Validation rules:
  - <rule> -> <action>
- Pivot design:
  - Rows/Columns/Values
  - Slicers
```

If asked for artifacts, also output:
- `assets/power-query-folder-ingest-template.pq` (adapted)
- `assets/refresh-checklist.md`


## SAFETY & EDGE CASES
- Read-only by default: provide a plan + snippets unless the user explicitly requests file generation.
- Never delete or overwrite user files; propose new filenames for outputs.
- Prefer “no silent failure”: include row-count checks and visible error flags.
- For PDF/DOCX sources, require user-provided exported tables (CSV/XLSX) or clearly mark extraction risk.


## EXAMPLES
- Input: “Folder of weekly CSVs with PayNumber/Name/Date.”  
  Output: Folder-ingest PQ template + schema + Refresh Status checks + pivot dashboard plan.

- Input: “Refresh breaks when new columns appear.”  
  Output: Defensive missing-column logic + column normalization + typed schema plan.