Skill audit report
Diagnose and plan Amazon Marketing Cloud (AMC) analytics and audience activation for European Amazon Ads accounts, including journey/path analysis, time to conversion, reach and frequency, ad-type overlap, new-to-brand, rule-based and lookalike audiences, seasonal off-peak audiences, and SP/SB/SD/DSP activation. Use for 欧洲站 AMC, 亚马逊营销云, AMC 人群包, 潮汐人群, 转化路径, 广告叠加, DSP+AMC, 购买转化周期, 新客分析, 受众竞价加成, AMC query/use case selection, 或把《欧洲转化破局》材料转为可审批的数据与投放方案. Default to read-only analysis and draft actions; never expose user-level data or mutate campaigns/audiences without verified scope and explicit human approval.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
FAIL30
16 GitHub stars
Stars/forks activity
FAIL32
16 stars, 1 forks; issue activity unavailable in current metadata
Recent maintenance
PASS88
2mo since push
License clarity
PASS86
MIT
README/SKILL.md completeness
INFO76
Public metadata needs stronger README/SKILL.md context
Dependency/runtime risk
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add xjli360/sealeap-amazon-ad-skills --skill sealeap-amazon-eu-amc-audience
Install command safety
PASS92
standard package or runtime install path
Permission surface
PASS86
filesystem or document access
Repository evidence
PASS86
https://github.com/xjli360/sealeap-amazon-ad-skills/tree/main/sealeap-amazon-eu-amc-audience
Review status
INFO66
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add xjli360/sealeap-amazon-ad-skills --skill sealeap-amazon-eu-amc-audience
Repository
88
https://github.com/xjli360/sealeap-amazon-ad-skills/tree/main/sealeap-amazon-eu-amc-audience
License
86
MIT
Maintenance
88
2mo since push
AI review
55
No critical issues found. The skill enforces read-only analysis by default, prohibits user-level data exposure, and requires explicit human approval before any mutation.
README/SKILL.md completeness
Warnings
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.
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Usable description available
Dependency risk
90
no major dependency risk hints in public metadata
Install command safety
92
standard package or runtime install path
Permission surface
86
filesystem or document access
Stars/forks activity
32
16 stars, 1 forks; issue activity unavailable in current metadata
Adoption
42
16 GitHub stars
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
Network access
mediumSkill likely fetches remote pages, APIs, repositories, or external services.
Filesystem access
mediumSkill may read or write project files, documents, generated artifacts, or local workspace state.
Database access
mediumSkill may inspect schemas, query databases, or work with persistent stores.