Skill audit report

Data Science For Beginners From Scratch Course Audit report.

Data science for beginners involves learning to extract insights from data using statistics, programming (Python/R), and visualization. Key steps include data collection, cleaning, analysis, modeling, and communicating findings. Beginners should start with Python, basic math (linear algebra/calculus), and build projects to create a portfolio.

REVIEWED · REVIEWNeeds reviewGenerated Nov 5, 2026Heuristic metadata audit

Audit

Trust

Quality

Security

Maintain

Install

OpenAgentSkill Trust Score

Strong shortlist

OpenAgentSkill Trust Score

The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.

GitHub adoption

INFO

183 GitHub stars

Stars/forks activity

INFO

183 stars, 146 forks; issue activity unavailable in current metadata

Recent maintenance

INFO

5mo since push

License clarity

PASS

MIT

README/SKILL.md completeness

PASS

Metadata includes enough usage and workflow context

Dependency/runtime risk

PASS

no major dependency risk hints in public metadata

Install availability

PASS

npx skills add SENATOROVAI/Data-Science-For-Beginners-from-scratch-course

Install command safety

PASS

standard package or runtime install path

Permission surface

PASS

filesystem or document access

Repository evidence

PASS

https://github.com/SENATOROVAI/Data-Science-For-Beginners-from-scratch-course

Review status

PASS

AI review data available

Agent Proven outcomes

INFO

No agent outcome data yet

Checks

Install and adoption review

8 Passed · 6 Needs review

Install path

PASS

npx skills add SENATOROVAI/Data-Science-For-Beginners-from-scratch-course

Repository

PASS

https://github.com/SENATOROVAI/Data-Science-For-Beginners-from-scratch-course

License

PASS

MIT

Maintenance

CHECK

5mo since push

AI review

PASS

Approved with no listed issues

README/SKILL.md completeness

PASS

Usable description available

Dependency risk

PASS

no major dependency risk hints in public metadata

Install command safety

PASS

standard package or runtime install path

Permission surface

PASS

filesystem or document access

Stars/forks activity

CHECK

183 stars, 146 forks; issue activity unavailable in current metadata

Adoption

INFO

183 GitHub stars

Financial decision safety

CHECK

Research-only use: do not treat output as financial advice or execute a position without human approval.

Warnings

Financial research output is not financial advice; require human review before any live investment decision
Financial research output is not financial advice; require human review before any live investment decision.
Quality score needs review

Method

This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.

Install path

Review the report before installing into production agents.

Review the source

Agent-readable metadata

Machine decision packet

Embedded JSON exposes suited tasks, suited agents, install command, trust score, safety gate, alternatives, and do-not-use conditions for agent review.

Install policy: review
Best agents: Python + Data Science
Alternatives: 3

Open agent JSON

Signals

Audit score: 80/100
Quality: 74/100
Trust: 79/100
Install safety: 92/100
Permission surface: 86/100
Maintenance: 5mo since push
Events: 21 events
GitHub stars: 183
Last push: Jun 19, 2026

Agent safety v2

64/100 · Avoid automatic install

Reviewed with permission notesreview

Usable candidate, but the agent should surface permission and audit notes before installation.

Skill source structure is not confirmed in the registry. Inspect the source and identify valid skill instructions before proposing an installation. A repository URL or GitHub stars do not prove installability.

Skill source structure is not confirmed in the registry. Inspect the source and identify valid skill instructions before proposing an installation. A repository URL or GitHub stars do not prove installability.
Financial research output is not financial advice; require human review before any live investment decision
64/100 agent safety score

Network access

medium

Skill likely fetches remote pages, APIs, repositories, or external services.

Filesystem access

medium

Skill may read or write project files, documents, generated artifacts, or local workspace state.

Financial research output is not financial advice; require human review before any live investment decision
Skill source structure is not confirmed in the registry. Inspect the source and identify valid skill instructions before proposing an installation. A repository URL or GitHub stars do not prove installability.

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