Skill audit report

appie-linkedin-growth Audit report.

Track LinkedIn profiles and list leads via Appie.run. Use when the user asks to track or stop tracking a LinkedIn profile, see which profiles are tracked, or list LinkedIn leads with their email or phone. Triggers include track this LinkedIn profile, LinkedIn leads, show my tracked profiles, stop tracking, lead emails, LinkedIn growth.

EXPERIMENTAL · REVIEWNeeds reviewGenerated Oct 20, 2026Heuristic metadata audit

Audit

Trust

Quality

Security

100

Maintain

Install

OpenAgentSkill Trust Score

Manual review

OpenAgentSkill Trust Score

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

GitHub adoption

FAIL

0 GitHub stars

Stars/forks activity

FAIL

0 stars, 0 forks; issue activity unavailable in current metadata

Recent maintenance

PASS

100

3d since push

License clarity

PASS

MIT

README/SKILL.md completeness

INFO

Public metadata needs stronger README/SKILL.md context

Dependency/runtime risk

INFO

credential or environment access, network or browser surface

Install availability

PASS

npx skills add appierun/appie-mcp --skill appie-linkedin-growth

Install command safety

PASS

standard package or runtime install path

Permission surface

WARN

secrets or environment access, network or browser access

Repository evidence

PASS

https://github.com/appierun/appie-mcp/tree/906374e88f676a33630debf04ed42b878b73de44/skills/appie-linkedin-growth

Review status

WARN

AI review approval is missing

Agent Proven outcomes

INFO

No agent outcome data yet

Checks

Install and adoption review

6 Passed · 14 Needs review

Install path

PASS

npx skills add appierun/appie-mcp --skill appie-linkedin-growth

Repository

PASS

https://github.com/appierun/appie-mcp/tree/906374e88f676a33630debf04ed42b878b73de44/skills/appie-linkedin-growth

License

PASS

MIT

Maintenance

100

PASS

3d since push

AI review

CHECK

Review approval is missing

README/SKILL.md completeness

PASS

Usable description available

Dependency risk

CHECK

credential or environment access, network or browser surface

Install command safety

PASS

standard package or runtime install path

Permission surface

CHECK

secrets or environment access, network or browser access

Stars/forks activity

FIX

0 stars, 0 forks; issue activity unavailable in current metadata

Adoption

CHECK

0 GitHub stars

Warnings

Permission surface may require sandboxing
Low GitHub adoption signal
AI review approval is missing
Quality score needs review
Permission surface needs review: secrets or environment access, network or browser access
GitHub adoption: 0 GitHub stars
Stars/forks activity: 0 stars, 0 forks; issue activity unavailable in current metadata
Permission surface: secrets or environment access, network or browser access
Review status: AI review approval is missing

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.

$ npx skills add appierun/appie-mcp --skill appie-linkedin-growth

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: Codex + Claude Code
Alternatives: 3

Open agent JSON

Signals

Audit score: 69/100
Quality: 41/100
Trust: 69/100
Install safety: 92/100
Permission surface: 60/100
Maintenance: 3d since push
Events: 5 events
GitHub stars: 0
Last push: Oct 17, 2026

Agent safety v2

45/100 · Avoid automatic install

Experimentalreview

Sparse or mixed signals. Useful for discovery, but not for autonomous installation.

Test manually in an isolated workspace and compare against safer alternatives.

High-risk permission hints: Secrets or environment access
45/100 agent safety score

Network access

medium

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

Secrets or environment access

high

Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.

High-risk permission hints: Secrets or environment access
Permission surface may require sandboxing

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