Laporan audit skill
python-code-reviewer Laporan audit.
Review, run, debug, and verify approved Python modeling code against its code plan, data contract, method decision, risk conditions, and experiment outputs, saving one compact JSON review.
Trust Score OpenAgentSkill
Trust Score OpenAgentSkill
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
Adopsi GitHub
Info76
695 star GitHub
Aktivitas star/fork
Info65
695 star dan 31 fork; aktivitas issue tidak tersedia dalam metadata saat ini
Pemeliharaan terbaru
Lulus88
2 bulan sejak push
Kejelasan lisensi
Lulus86
MIT
Kelengkapan README/SKILL.md
Info76
Metadata publik memerlukan konteks README/SKILL.md yang lebih kuat
Risiko dependensi/runtime
Lulus90
Tidak ada petunjuk risiko dependensi besar dalam metadata publik
Ketersediaan pemasangan
Lulus92
npx skills add zhnnky329/MathModeling-skills --skill python-code-reviewer
Keamanan perintah pemasangan
Lulus92
Jalur pemasangan paket atau runtime standar
Cakupan izin
Lulus88
Akses database
Bukti repositori
Lulus86
https://github.com/zhnnky329/MathModeling-skills/tree/main/.claude/skills/python-code-reviewer
Status peninjauan
Lulus88
Data tinjauan AI tersedia
Hasil terbukti Agent
Info54
Belum ada data hasil Agent
Pemeriksaan
Tinjauan pemasangan dan adopsi
Jalur pemasangan
92
npx skills add zhnnky329/MathModeling-skills --skill python-code-reviewer
Repositori
88
https://github.com/zhnnky329/MathModeling-skills/tree/main/.claude/skills/python-code-reviewer
Lisensi
86
MIT
Pemeliharaan
88
2 bulan sejak push
Tinjauan AI
88
Approved with no listed issues
Kelengkapan README/SKILL.md
84
Usable description available
Risiko dependensi
90
Tidak ada petunjuk risiko dependensi besar dalam metadata publik
Keamanan perintah pemasangan
92
Jalur pemasangan paket atau runtime standar
Cakupan izin
88
Akses database
Aktivitas star/fork
65
695 star dan 31 fork; aktivitas issue tidak tersedia dalam metadata saat ini
Adopsi
88
695 star GitHub
Peringatan
- Quality score needs review
Metode
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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