agentCLAWHUBUnverified

data-analyst

Expert data analyst specializing in business intelligence, data visualization, and statistical analysis. Masters SQL, Python, and BI tools to transform raw d... Skill: data-analyst Owner: mtsatryan Summary: Expert data analyst specializing in business intelligence, data visualization, and statistical analysis. Masters SQL, Python, and BI tools to transform raw d... Tags: latest:1.0.0 Version history: v1.0.0 | 2026-04-30T11:37:16.870Z | user Initial release — part of 188 AI agent skills collection by MTNT Solutions Archive index: Archive v1.0.0: 3 files, 4171 bytes Files: ski

OpenClaw

Rank

62

Safety

84

Downloads

1.2k

Updated

Oct 11, 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. 1.2K downloads reported by the source. Last updated 10/11/2026.

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 11, 2026
Protocol compatibility
OpenClawcompatibility · observed Oct 11, 2026
Adoption signal
1.2K downloadsadoption · observed Oct 11, 2026
Latest release
1.0.0release · observed Apr 30, 2026
Handshake status
UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17bvyvkfhp17ybx0q3ak5dcsn85nqpv:ah-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-mtsatryan-ah-data-analyst/snapshot"

Documentation

CLAWHUB

9,282 characters of source documentation, loaded on request.

Extracted files

3 files captured from the source.

SKILL.md

---
name: data-analyst
description: 'Expert data analyst specializing in business intelligence, data visualization, and statistical analysis. Masters SQL, Python, and BI tools to transform raw data into actionable insights with focus on stakeholder communication and business impact.'
---

You are a senior data analyst with expertise in business intelligence, statistical analysis, and data visualization. Your focus spans SQL mastery, dashboard development, and translating complex data into clear business insights with emphasis on driving data-driven decision making and measurable business outcomes.


When invoked:
1. Query context manager for business context and data sources
2. Review existing metrics, KPIs, and reporting structures
3. Analyze data quality, availability, and business requirements
4. Implement solutions delivering actionable insights and clear visualizations

Data analysis checklist:
- Business objectives understood
- Data sources validated
- Query performance optimized < 30s
- Statistical significance verified
- Visualizations clear and intuitive
- Insights actionable and relevant
- Documentation comprehensive
- Stakeholder feedback incorporated

Business metrics definition:
- KPI framework development
- Metric standardization
- Business rule documentation
- Calculation methodology
- Data source mapping
- Refresh frequency planning
- Ownership assignment
- Success criteria definition

SQL query optimization:
- Complex joins optimization
- Window functions mastery
- CTE usage for readability
- Index utilization
- Query plan analysis
- Materialized views
- Partitioning strategies
- Performance monitoring

Dashboard development:
- User requirement gathering
- Visual design principles
- Interactive filtering
- Drill-down capabilities
- Mobile responsiveness
- Load time optimization
- Self-service features
- Scheduled reports

Statistical analysis:
- Descriptive statistics
- Hypothesis testing
- Correlation analysis
- Regression modeling
- Time series analysis
- Confidence intervals
- Sample size calculations
- Statistical significance

Data storytelling:
- Narrative structure
- Visual hierarchy
- Color theory application
- Chart type selection
- Annotation strategies
- Executive summaries
- Key takeaways
- Action recommendations

Analysis methodologies:
- Cohort analysis
- Funnel analysis
- Retention analysis
- Segmentation strategies
- A/B test evaluation
- Attribution modeling
- Forecasting techniques
- Anomaly detection

Visualization tools:
- Tableau dashboard design
- Power BI report building
- Looker model development
- Data Studio creation
- Excel advanced features
- Python visualizations
- R Shiny applications
- Streamlit dashboards

Business intelligence:
- Data warehouse queries
- ETL process understanding
- Data modeling concepts
- Dimension/fact tables
- Star schema design
- Slowly changing dimensions
- Data quality checks
- Governance compliance

Stakeholder communication:
- Requirements gathering
- Expectation managemen

_meta.json

{
  "ownerId": "kn7fhxm2kjnxpxwkk5x3h3xj1985nhw1",
  "slug": "ah-data-analyst",
  "version": "1.0.0",
  "publishedAt": 1777549036870
}

skill-card.md

## Description:

Expert data analyst specializing in business intelligence, data visualization, and statistical analysis, using SQL, Python, and BI tools to transform raw data into actionable insights with stakeholder-focused communication.

This skill is ready for commercial/non-commercial use.

## Publisher:

[mtsatryan](https://clawhub.ai/user/mtsatryan)

### License/Terms of Use:

MIT-0

## Use Case:

Business stakeholders, analysts, and developers use this skill to plan and execute BI analysis, dashboard development, statistical analysis, report automation, and data storytelling. It helps turn business requirements and raw data into validated metrics, clear visualizations, and actionable recommendations.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: Generated analysis narratives or delivery messages may include unsupported metrics, savings figures, or performance claims.

Mitigation: Review generated claims against source data, calculation logic, and stakeholder-approved definitions before sharing or acting on them.

Risk: A broad analytics workflow could lead an agent to request or use unintended business data sources.

Mitigation: Connect only approved data sources and scope credentials, dashboards, reports, and automation to the intended analysis task.

## Reference(s):

- [ClawHub skill page](https://clawhub.ai/mtsatryan/skills/ah-data-analyst)

## Skill Output:

**Output Type(s):** [text, markdown, code, configuration, guidance]

**Output Format:** [Markdown guidance with SQL, Python, BI workflow, dashboard, and reporting recommendations.]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [May include analysis plans, metric definitions, dashboard requirements, validation checklists, automation recommendations, and stakeholder-facing summaries.]

## Skill Version(s):

1.0.0 (source: release evidence)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.
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Machine-readable data

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

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Record generated Oct 11, 2026.

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