What makes Excel Data Quality Check notable?

1.9K downloads. Trust evidence available

How should Excel Data Quality Check be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

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agentCLAWHUBUnverified

Excel Data Quality Check

Excel/CSV data quality diagnosis & interactive charts — 20+ scan modules, 6-dimension scoring, agent-powered semantic analysis, and any ECharts visualization... Skill: Excel Data Quality Check Owner: chartgen-ai Summary: Excel/CSV data quality diagnosis & interactive charts — 20+ scan modules, 6-dimension scoring, agent-powered semantic analysis, and any ECharts visualization... Tags: latest:1.0.0 Version history: v1.0.0 | 2026-03-30T12:33:14.704Z | user - Initial release of Excel Data Helper — perform local Excel/CSV data profiling, quality scanning, and chart generation wi

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.9k

Updated

Oct 9, 2026

Version

1.0.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.9K downloads reported by the source. Last updated 10/9/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 9, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 9, 2026
Adoption signal: 1.9K downloadsadoption · observed Oct 9, 2026
Latest release: 1.0.0release · observed Mar 30, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s1760v3fs4sg6tdv3k9gq9792h83h5yy:excel-data-quality

Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-chartgen-ai-excel-data-quality/snapshot"

Documentation

CLAWHUB

31,566 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: excel-data-helper
description: >
  Excel/CSV data quality diagnosis & interactive charts — 20+ scan modules, 6-dimension scoring, agent-powered semantic analysis, and any ECharts visualization. Fully local.
  Activate this skill whenever the user uploads, attaches, or mentions a .csv, .xlsx, .xls, or .tsv file, even without an explicit request. Present the skill menu immediately.
user-invocable: true
homepage: https://github.com/excel-data-helper/excel-data-helper-skill
metadata:
  openclaw:
    requires:
      runtime:
        - node >= 14
---

# Excel Data Helper — Data Quality Diagnosis & Chart Skill

Local Excel/CSV data profiling, quality scanning (20+ modules, 6-dimension scoring, LLM semantic analysis), and chart generation. International locale support: CJK, European, Middle Eastern, Americas.

**Supported files**: `.csv` `.tsv` `.xlsx` `.xls`

---

## Trigger & Menu

When a supported file is detected, **do not auto-process** — present this menu first (adapt to the user's language):

> **📊 Excel Data Helper** — Hi, I noticed you shared a data file: `<filename>`
>
> | # | Action | Description |
> |:---:|--------|-------------|
> | **1** | Quality Check | Overview, scan, scoring |
> | **2** | Chart | Any ECharts type: bar, line, pie, scatter, radar, heatmap… |
> | **3** | Advanced Chart | Dashboard, Gantt, PPT, diagrams |
> | **0** | Skip | Do nothing for now |
>
> Reply 0–3, or describe what you need.

---

## Routing & Context

Match user intent and route to the corresponding sub-skill:

- IF user replies `1`, or intent is **overview / quality check / diagnose / score / problems**
  → follow `references/quality-check.md`

- IF user replies `2`, or intent is **chart / plot / visualize / graph**
  → follow `references/chart.md`

- IF user replies `3`, or intent is **dashboard / Gantt / PPT / diagram / complex layout**
  → follow `references/advanced-chart.md`

- IF user replies `0`, or intent is **skip / later / not now**
  → do nothing, reply: "Got it — file noted. Just let me know when you're ready."

- IF intent is **ambiguous or unrelated** → ask to clarify, never guess.

Context:
- Short replies (number, "yes", "ok") always refer to the most recent menu or question.
- After Skip (0), context resets — ignore the file unless user re-references it.
- Multiple files — each needs its own explicit choice.

---

## Setup

Before first use, install dependencies (one-time):

```bash
cd <skill_directory>
npm install
```

This installs `xlsx` (SheetJS), `echarts`, and `sharp`. All analysis and chart rendering runs locally.

---

## Rules

- Respond in the user's language.
- Never auto-process a file — wait for explicit choice.
- Parse tool JSON output; present results in clear, readable format — never expose raw JSON.
- Use absolute file paths from tool output directly for follow-up operations.
- Always include "Excel Data Helper" in the menu header.

README.md

# Excel Data Helper — Data Quality Diagnosis & Chart Skill

> **Fully local** Excel/CSV data overview, quality diagnosis, and charting — no API key needed.

A skill for [OpenClaw](https://openclaw.com) and other AI agents that provides comprehensive data quality analysis and charting capabilities, powered entirely by local Node.js tools.

---

## What Can It Do?

### 1. Quality Check (22 Scan Modules, 6-Dimension Scoring, LLM Semantic Analysis)
Upload a CSV/Excel file and get a complete data profile (column types, null rates, unique values, patterns, statistics) plus a quality scan across six dimensions:
- **Completeness**: null values, empty strings, empty rows, merged cell patterns
- **Accuracy**: outliers (IQR), rare values, value uniformity (zero-variance / dominant value)
- **Consistency**: mixed types, case issues, date formats, full-width/half-width chars, numbers with embedded units, cross-column logical checks
- **Validity**: email/phone format (intl.), special characters, range checks, encoding/mojibake detection, ID card checksum validation
- **Uniqueness**: duplicate rows, primary key violations, near-duplicate (fuzzy) value detection with Unicode normalization
- **Timeliness**: future dates, abnormally old dates

**International locale support**: multilingual field name recognition (EN, ZH, JA, KO, ES, FR, DE, AR), international date formats (ISO, EU DD.MM.YYYY, US MM/DD/YYYY, CJK 年月日, Korean 년월일, Japanese era), global currency symbols (¥ $ € £ ₩ ₹ ₽ etc.), and region-specific quality patterns.

Plus LLM-powered semantic analysis: synonym detection (cross-language), multi-value cells, business key analysis, cross-column relationship insights, locale-specific observations, and data fitness assessment.

Get a weighted quality score (0-100) with grade, breakdown, and actionable recommendations.

### 2. Charts
Generate PNG chart images (server-side ECharts rendering):
- Any ECharts chart type: bar, line, pie, scatter, area, radar, boxplot, heatmap, funnel, treemap, combo, and more
- LLM analyzes data and determines the best 1–5 charts with optimal types and configs
- PNG images sent directly in conversation — no browser needed

### 3. Advanced Charts (via ChartGen)
For dashboards, Gantt charts, diagrams, and PPT — delegates to the ChartGen skill (requires API key).

---

## Installation

### Natural Language Install (OpenClaw)

> Install this skill for me: `https://github.com/excel-data-helper/excel-data-helper-skill.git`

### Manual Installation

```bash
cd ~/.openclaw/workspace/skills
git clone https://github.com/excel-data-helper/excel-data-helper-skill.git
cd excel-data-helper-skill
npm install
```

---

## Usage Examples

### Quality Check
> "What's in this Excel file?"
> "Check the data quality of this file"
> "Are there any problems with my data?"

### Charts
> "Create a bar chart of sales by category"
> "Suggest some charts for this data"

---

## Tools

| Tool |

_meta.json

{
  "ownerId": "kn71r1x7xjwqg75w376gzjx0pn82peh5",
  "slug": "excel-data-quality",
  "version": "1.0.0",
  "publishedAt": 1774873994704
}

references/advanced-chart.md

# Advanced Chart — Sub-Skill

## When to Use

User needs complex visualizations that go beyond basic charts:
- **Dashboards** with multiple charts in a layout
- **Gantt charts** for project timelines
- **Diagrams** (flowchart, sequence, ER, mind map)
- **PPT generation** with embedded visualizations
- **Advanced analysis** (YoY, cross-file joins, trend analysis)
- **Professional themes** and export options

## Implementation

This capability delegates to the **ChartGen** skill, which provides AI-powered visualization via the ChartGen API.

### Step 1 — Check ChartGen Availability

Verify that the `chartgen` skill is installed and configured. Look for the skill at:
- `../chartgen-skill/SKILL.md` (sibling directory)
- Or installed via OpenClaw's skill system

### Step 2 — If ChartGen is Available

Follow the ChartGen skill's workflow:

1. Read and follow the instructions in the ChartGen `SKILL.md`
2. The ChartGen skill handles:
   - Confirming the request with the user
   - Submitting to ChartGen API
   - Polling for results
   - Delivering artifacts (images, PPT, dashboards)

**Important**: ChartGen requires an API key. If not configured, it will provide setup instructions.

### Step 3 — If ChartGen is NOT Available

Inform the user and offer alternatives:

> The advanced chart capability requires **ChartGen AI** which is not currently installed.
>
> **Options:**
> 1. **Install ChartGen**: Tell me "install skill https://github.com/chartgen-ai/chartgen-skill.git"
> 2. **Use basic charts**: I can create bar, line, pie, scatter, and area charts locally (no API needed)
> 3. **Export data**: I can clean and export your data for use in other visualization tools

### Fallback to Basic Charts

If the user's request can be partially fulfilled with basic charts:

> Your request involves a dashboard layout, which needs ChartGen. However, I can create individual charts locally:
> - A line chart for the time-series data
> - A bar chart for the category comparison
>
> Want me to create these basic charts instead?

## ChartGen Capabilities Reference

When ChartGen is available, it supports:

| Type | Output | Description |
|------|--------|-------------|
| Charts | PNG | All ECharts types: bar, line, pie, scatter, heatmap, radar, treemap, etc. |
| Diagrams | PNG | Flowchart, sequence, class, state, ER, mind map, timeline |
| Dashboards | PNG/HTML | Multi-chart interactive layouts |
| Gantt | PNG | Project timelines with dependencies |
| PPT | PPTX | Presentation slides with visualizations |
| Reports | Text + Charts | Analysis reports with insights |

references/chart.md

# Chart — Sub-Skill

## Tool

### Inspect data (planning only)

```bash
node tools/chart_renderer.js <file_path> --info
```

Returns column names, inferred types, stats (min/max/mean, unique count, sample values, date range). Use this to understand the data before deciding what to chart.

### Render a chart

```bash
node tools/chart_renderer.js <file_path> --config '<json>' [--output <path>]
```

Outputs a **PNG image** file. The tool only renders — all chart-type decisions, column selection, and ECharts customization are made by YOU in the config JSON.

---

## Config JSON Schema

```jsonc
{
  "type": "bar",                   // REQUIRED — see Supported Types below
  "x": "column_name",             // X-axis / group column
  "y": "col" or ["col1","col2"],  // Y-axis / value column(s)
  "title": "Chart Title",         // shown at top of chart
  "xName": "X Label",             // axis label
  "yName": "Y Label",
  "aggregate": "sum",             // for pie/funnel/treemap: sum|avg|count|max|min
  "series": [                     // optional per-series overrides
    {
      "name": "Display Name",
      "type": "line",             // override type for combo charts
      "smooth": true,
      "area": true,               // fill area below line
      "stack": "group1",
      "itemStyle": { "color": "#ee6666" },
      "label": { "show": true },
      "markLine": { "data": [{ "type": "average" }] },
      "markPoint": { "data": [{ "type": "max" }, { "type": "min" }] }
    }
  ],
  "value": "col",                 // for heatmap: the value (intensity) column
  "radius": "60%",                // for pie
  "roseType": "area",             // for nightingale rose pie
  "symbolSize": 10,               // for scatter
  "width": 900,                   // image width in px
  "height": 600,                  // image height in px
  "limit": 500,                   // max rows (default 500)
  "echarts": { }                  // raw ECharts option — deep-merged last, overrides everything
}
```

### Supported Types

| Type | x | y | Notes |
|------|---|---|-------|
| `bar` | category | numeric(s) | grouped / stacked via `series[].stack` |
| `line` | category / date | numeric(s) | `smooth`, `area` |
| `area` | category / date | numeric(s) | shortcut for line + areaStyle |
| `pie` | category | numeric | auto-aggregates by x; `roseType` for nightingale |
| `scatter` | numeric | numeric | `symbolSize` |
| `radar` | — | numeric[] | y = array of metric columns |
| `boxplot` | — | numeric[] | y = array of columns to box-plot |
| `heatmap` | category | category | requires `value` (z) column |
| `funnel` | category | numeric | sorted descending |
| `treemap` | category | numeric | hierarchical area |
| `combo` | category | numeric[] | use `series[].type` to mix bar/line |

For any ECharts type not listed above (gauge, sankey, graph, sunburst…), pass a complete option object via the `echarts` field — it deep-

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