Laporan audit skill
qdrant-sizing Laporan audit.
Sizes a Qdrant deployment before it is provisioned. Use when someone asks 'how much RAM do I need', 'how many nodes', 'how big should my cluster be', 'sizing', 'capacity planning', 'will N vectors fit', 'what instance type should I pick', or gives a vector count and dimensions and asks what to provision. Also use when an existing estimate needs checking before hardware or a cluster tier is bought.
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
Info62
253 star GitHub
Aktivitas star/fork
Peringatan57
253 star dan 30 fork; aktivitas issue tidak tersedia dalam metadata saat ini
Pemeliharaan terbaru
Lulus100
13 hari sejak push
Kejelasan lisensi
Lulus86
Apache-2.0
Kelengkapan README/SKILL.md
Lulus86
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 qdrant/skills --skill qdrant-sizing
Keamanan perintah pemasangan
Lulus92
Jalur pemasangan paket atau runtime standar
Cakupan izin
Lulus100
Tidak ada cakupan izin berisiko tinggi dalam metadata publik
Bukti repositori
Lulus86
https://github.com/qdrant/skills/tree/main/skills/qdrant-sizing
Status peninjauan
Info66
Data tinjauan AI tersedia
Hasil terbukti Agent
Info54
Belum ada data hasil Agent
Pemeriksaan
Tinjauan pemasangan dan adopsi
Jalur pemasangan
92
npx skills add qdrant/skills --skill qdrant-sizing
Repositori
88
https://github.com/qdrant/skills/tree/main/skills/qdrant-sizing
Lisensi
86
Apache-2.0
Pemeliharaan
100
13 hari sejak push
Tinjauan AI
55
The simplified RAM formula `number_of_vectors × dimension × 4 × 1.5` does not explicitly include `replication_factor`, while the detailed footprint section correctly uses `base = points × replication_factor`. This could lead to undersizing replicated deployments if an agent uses the rough formula alone.
Kelengkapan README/SKILL.md
86
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
100
Tidak ada cakupan izin berisiko tinggi dalam metadata publik
Aktivitas star/fork
57
253 star dan 30 fork; aktivitas issue tidak tersedia dalam metadata saat ini
Adopsi
68
253 star GitHub
Peringatan
- The simplified RAM formula `number_of_vectors × dimension × 4 × 1.5` does not explicitly include `replication_factor`, while the detailed footprint section correctly uses `base = points × replication_factor`. This could lead to undersizing replicated deployments if an agent uses the rough formula alone.
- Disk sizing guidance is high-level and does not give concrete allowances for WAL, snapshots, recovery, or temporary segment overhead beyond the general data footprint.
- Memory tier version details (1.19+ vs 1.18 and older) and other version-specific statements may become stale without a review date or compatibility note.
- Quality score needs review
- Stars/forks activity: 253 stars, 30 forks; issue activity unavailable in current metadata
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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