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DataScience Interview Questions Audit Report | OpenAgentSkill | OpenAgentSkill

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Skills/DataScience Interview Questions/Audit

Skill audit report

DataScience Interview Questions Audit report.

My Solutions to 120 commonly asked data science interview questions.

EXPERIMENTAL · REVIEWNeeds reviewGenerated Oct 9, 2026Heuristic metadata audit

63

Audit

71

Trust

50

Quality

87

Security

20

Maintain

92

Install

OpenAgentSkill Trust Score

71

The skill layer for AI agents: discover, compare, audit, and install reusable capabilities across Codex, Claude Code, Cursor, and agent runtimes.

Explore

Skills Gallery New submissions Agent Skills

More links

What Is an Agent Skill?AI Agent Skills Tasks Packs Best Skills New & Trending Workflow Recipes Use Cases Agents Agent Entry

Trust

Compare Safety Gate Skills Registry Rankings

More links

Outcome Loop Audits Official Weekly Reports Monthly Index State of Agent Skills vs skills.sh AgentSkills.io Alternative

Build

Docs About Contact Sponsor API

More links

llms.txt OpenAPI CLI Creator Kit Skill Creators X Growth Kit Submit Blog Guides Activity

OpenAgentSkill Registry

Privacy Contact SponsorBuilt for agent-native discovery

Manual review

OpenAgentSkill Trust Score

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

GitHub adoption

INFO

62

228 GitHub stars

Stars/forks activity

INFO

62

228 stars, 182 forks; issue activity unavailable in current metadata

Recent maintenance

FAIL

22

4y since push

License clarity

PASS

86

MIT

README/SKILL.md completeness

INFO

74

Public metadata needs stronger README/SKILL.md context

Dependency/runtime risk

PASS

90

no major dependency risk hints in public metadata

Install availability

PASS

92

npx skills add milaan9/DataScience_Interview_Questions

Install command safety

PASS

92

standard package or runtime install path

Permission surface

PASS

86

filesystem or document access

Repository evidence

PASS

86

https://github.com/milaan9/DataScience_Interview_Questions

Review status

PASS

88

AI review data available

Agent Proven outcomes

INFO

54

No agent outcome data yet

Checks

Install and adoption review

8 Passed · 9 Needs review

Install path

92

PASS

npx skills add milaan9/DataScience_Interview_Questions

Repository

88

PASS

https://github.com/milaan9/DataScience_Interview_Questions

License

86

PASS

MIT

Maintenance

20

FIX

4y since push

AI review

88

PASS

Approved with no listed issues

README/SKILL.md completeness

84

PASS

Usable description available

Dependency risk

90

PASS

no major dependency risk hints in public metadata

Install command safety

92

PASS

standard package or runtime install path

Permission surface

86

PASS

filesystem or document access

Stars/forks activity

62

CHECK

228 stars, 182 forks; issue activity unavailable in current metadata

Adoption

68

INFO

228 GitHub stars

Financial decision safety

58

CHECK

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

Warnings

Repository appears stale
Financial research output is not financial advice; require human review before any live investment decision
Repository looks stale
Financial research output is not financial advice; require human review before any live investment decision.
Quality score needs review
Recent maintenance: 4y since push

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: Jupyter Notebook + Data Analysis
Alternatives: 3

Open agent JSON

Signals

Audit score: 63/100
Quality: 50/100
Trust: 71/100
Install safety: 92/100
Permission surface: 86/100
Maintenance: 4y since push
Events: 11 events
GitHub stars: 228
Last push: Dec 9, 2022

Agent safety v2

47/100 · Avoid automatic install

Experimentalreview

Sparse or mixed signals. Useful for discovery, but not for autonomous 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.
Repository appears stale
47/100 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.

Repository appears stale
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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