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Data Analyst

Data visualization, report generation, SQL queries, and spreadsheet automation. Transform your AI agent into a data-savvy analyst that turns raw data into actionable insights. Skill: Data Analyst Owner: oyi77 Summary: Data visualization, report generation, SQL queries, and spreadsheet automation. Transform your AI agent into a data-savvy analyst that turns raw data into actionable insights. Tags: latest:1.0.0 Version history: v1.0.0 | 2026-02-06T20:42:17.278Z | auto Initial release of the Data Analyst skill: - Provides SQL query patterns for common analyses, including cohort and funnel ana

View on ClawHub

Rank

62

Safety

84

Downloads

7.4k

Updated

Apr 15, 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. 7.4K downloads reported by the source. Last updated 4/15/2026.

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 Apr 15, 2026
Adoption signal
7.4K downloadsadoption · observed Apr 15, 2026
Latest release
1.0.0release · observed Feb 6, 2026
Handshake status
UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install kn7cpmgq5bpf1mp69bpd7n9as180nssd:data-analyst
  1. Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
  2. 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-oyi77-data-analyst/snapshot"

Documentation

CLAWHUB

14,693 characters of source documentation, loaded on request.

Extracted files

2 files captured from the source.

SKILL.md

---
name: data-analyst
version: 1.0.0
description: "Data visualization, report generation, SQL queries, and spreadsheet automation. Transform your AI agent into a data-savvy analyst that turns raw data into actionable insights."
author: openclaw
---

# Data Analyst Skill 📊

**Turn your AI agent into a data analysis powerhouse.**

Query databases, analyze spreadsheets, create visualizations, and generate insights that drive decisions.

---

## What This Skill Does

✅ **SQL Queries** — Write and execute queries against databases
✅ **Spreadsheet Analysis** — Process CSV, Excel, Google Sheets data
✅ **Data Visualization** — Create charts, graphs, and dashboards
✅ **Report Generation** — Automated reports with insights
✅ **Data Cleaning** — Handle missing data, outliers, formatting
✅ **Statistical Analysis** — Descriptive stats, trends, correlations

---

## Quick Start

1. Configure your data sources in `TOOLS.md`:
```markdown
### Data Sources
- Primary DB: [Connection string or description]
- Spreadsheets: [Google Sheets URL / local path]
- Data warehouse: [BigQuery/Snowflake/etc.]
```

2. Set up your workspace:
```bash
./scripts/data-init.sh
```

3. Start analyzing!

---

## SQL Query Patterns

### Common Query Templates

**Basic Data Exploration**
```sql
-- Row count
SELECT COUNT(*) FROM table_name;

-- Sample data
SELECT * FROM table_name LIMIT 10;

-- Column statistics
SELECT 
    column_name,
    COUNT(*) as count,
    COUNT(DISTINCT column_name) as unique_values,
    MIN(column_name) as min_val,
    MAX(column_name) as max_val
FROM table_name
GROUP BY column_name;
```

**Time-Based Analysis**
```sql
-- Daily aggregation
SELECT 
    DATE(created_at) as date,
    COUNT(*) as daily_count,
    SUM(amount) as daily_total
FROM transactions
GROUP BY DATE(created_at)
ORDER BY date DESC;

-- Month-over-month comparison
SELECT 
    DATE_TRUNC('month', created_at) as month,
    COUNT(*) as count,
    LAG(COUNT(*)) OVER (ORDER BY DATE_TRUNC('month', created_at)) as prev_month,
    (COUNT(*) - LAG(COUNT(*)) OVER (ORDER BY DATE_TRUNC('month', created_at))) / 
        NULLIF(LAG(COUNT(*)) OVER (ORDER BY DATE_TRUNC('month', created_at)), 0) * 100 as growth_pct
FROM transactions
GROUP BY DATE_TRUNC('month', created_at)
ORDER BY month;
```

**Cohort Analysis**
```sql
-- User cohort by signup month
SELECT 
    DATE_TRUNC('month', u.created_at) as cohort_month,
    DATE_TRUNC('month', o.created_at) as activity_month,
    COUNT(DISTINCT u.id) as users
FROM users u
LEFT JOIN orders o ON u.id = o.user_id
GROUP BY cohort_month, activity_month
ORDER BY cohort_month, activity_month;
```

**Funnel Analysis**
```sql
-- Conversion funnel
WITH funnel AS (
    SELECT
        COUNT(DISTINCT CASE WHEN event = 'page_view' THEN user_id END) as views,
        COUNT(DISTINCT CASE WHEN event = 'signup' THEN user_id END) as signups,
        COUNT(DISTINCT CASE WHEN event = 'purchase' THEN user_id END) as purchases
    FROM events
    WHERE date >= CURRENT_DATE - INTERVAL '30 days'

_meta.json

{
  "ownerId": "kn7cpmgq5bpf1mp69bpd7n9as180nssd",
  "slug": "data-analyst",
  "version": "1.0.0",
  "publishedAt": 1770410537278
}

Machine-readable data

The same record, as JSON, for agents and crawlers.

{
  "facts": [
    {
      "factKey": "vendor",
      "category": "vendor",
      "label": "Vendor",
      "value": "Clawhub",
      "href": "https://clawhub.ai/oyi77/data-analyst",
      "sourceUrl": "https://clawhub.ai/oyi77/data-analyst",
      "sourceType": "profile",
      "confidence": "medium",
      "observedAt": "2026-04-15T00:45:39.800Z",
      "isPublic": true
    },
    {
      "factKey": "traction",
      "category": "adoption",
      "label": "Adoption signal",
      "value": "7.4K downloads",
      "href": "https://clawhub.ai/oyi77/data-analyst",
      "sourceUrl": "https://clawhub.ai/oyi77/data-analyst",
      "sourceType": "profile",
      "confidence": "medium",
      "observedAt": "2026-04-15T00:45:39.800Z",
      "isPublic": true
    },
    {
      "factKey": "latest_release",
      "category": "release",
      "label": "Latest release",
      "value": "1.0.0",
      "href": "https://clawhub.ai/oyi77/data-analyst",
      "sourceUrl": "https://clawhub.ai/oyi77/data-analyst",
      "sourceType": "release",
      "confidence": "medium",
      "observedAt": "2026-02-06T20:42:17.278Z",
      "isPublic": true
    },
    {
      "factKey": "handshake_status",
      "category": "security",
      "label": "Handshake status",
      "value": "UNKNOWN",
      "href": "https://www.xpersona.co/api/v1/agents/clawhub-oyi77-data-analyst/trust",
      "sourceUrl": "https://www.xpersona.co/api/v1/agents/clawhub-oyi77-data-analyst/trust",
      "sourceType": "trust",
      "confidence": "medium",
      "observedAt": null,
      "isPublic": true
    }
  ],
  "events": [
    {
      "eventType": "release",
      "title": "Release 1.0.0",
      "description": "Initial release of the Data Analyst skill: - Provides SQL query patterns for common analyses, including cohort and funnel analysis. - Enables spreadsheet processing and data cleaning techniques. - Offers Python code samples for data analysis and visualization. - Includes guides for chart selection and terminal-friendly ASCII charts. - Delivers templates and checklists for data audits and report generation.",
      "href": "https://clawhub.ai/oyi77/data-analyst",
      "sourceUrl": "https://clawhub.ai/oyi77/data-analyst",
      "sourceType": "release",
      "confidence": "medium",
      "observedAt": "2026-02-06T20:42:17.278Z",
      "isPublic": true
    }
  ]
}

Record generated Oct 9, 2026.

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