Laporan audit skill
LinearRAG Laporan audit.
[ICLR 2026] LinearRAG: Linear Graph Retrieval Augmented Generation on Large-scale Corpora
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
507 star GitHub
Aktivitas star/fork
Info71
507 star dan 59 fork; aktivitas issue tidak tersedia dalam metadata saat ini
Pemeliharaan terbaru
Info76
5 bulan sejak push
Kejelasan lisensi
Lulus86
GPL-3.0
Kelengkapan README/SKILL.md
Lulus90
Metadata memuat konteks penggunaan dan alur kerja yang cukup
Risiko dependensi/runtime
Lulus90
Tidak ada petunjuk risiko dependensi besar dalam metadata publik
Ketersediaan pemasangan
Lulus92
npx skills add DEEP-PolyU/LinearRAG
Keamanan perintah pemasangan
Lulus92
Jalur pemasangan paket atau runtime standar
Cakupan izin
Lulus86
Akses sistem file atau dokumen
Bukti repositori
Lulus86
https://github.com/DEEP-PolyU/LinearRAG
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 DEEP-PolyU/LinearRAG
Repositori
88
https://github.com/DEEP-PolyU/LinearRAG
Lisensi
86
GPL-3.0
Pemeliharaan
76
5 bulan sejak push
Tinjauan AI
88
Approved with no listed issues
Kelengkapan README/SKILL.md
90
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
86
Akses sistem file atau dokumen
Aktivitas star/fork
71
507 star dan 59 fork; aktivitas issue tidak tersedia dalam metadata saat ini
Adopsi
88
507 star GitHub
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Peringatan
- 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
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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