OpenAgentSkill
GitHub200+

Evaluasi sebelum pemasangan

qdrant-sizing Laporan evaluasi.

Keputusan pemasangan yang dapat dibaca mesin untuk Agent: kecocokan tugas, Trust Score, Audit Score, keamanan pemasangan, cakupan izin, dan rencana validasi konkret sebelum skill menyentuh workspace.

Perlu ditinjauRisiko sedangTinjau Kebijakan
73
Laporan evaluasi
73
Kepercayaan
80
Audit
64
Keamanan Agent

Tinjauan manual

Memerlukan persetujuan manusia sebelum memasang ke workspace nyata.

Gerbang wajib

Pemeriksaan yang harus dilalui Agent sebelum memasang

Buka JSON

Kecocokan tugas

84

Lulus

Task wording matches this skill metadata.

  • Evaluate qdrant-sizing before installing it in an agent workflow
  • automation
  • RAG and knowledge workflows; Claude Code teams; builders willing to evaluate younger projects

Jalur pemasangan

92

Lulus

Install handoff is available.

  • npx skills add qdrant/skills --skill qdrant-sizing

Keamanan perintah pemasangan

92

Lulus

Jalur pemasangan paket atau runtime standar

  • npx skills add qdrant/skills --skill qdrant-sizing

Skor kepercayaan

73

Peringatan

Good trust signals with a few areas worth checking before rollout.

  • Shortlist kuat
  • 253 star GitHub
  • Apache-2.0

Skor audit

80

Peringatan

Perlu ditinjau

  • 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.

Gerbang keamanan Agent

64

Peringatan

Kandidat yang dapat digunakan, tetapi Agent harus menampilkan catatan izin dan audit sebelum memasang.

  • Memerlukan persetujuan manusia sebelum memasang ke workspace nyata.
  • 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.

Kejelasan lisensi

86

Lulus

Apache-2.0

  • Apache-2.0

Cakupan izin

100

Lulus

Tidak ada cakupan izin berisiko tinggi dalam metadata publik

  • Network access: medium
  • Database access: medium

Rencana validasi

Langkah Agent berikutnya

  1. 1Inspect repository, README/SKILL.md, license, and recent commits before production use.
  2. 2Install in an isolated workspace or sandbox with no production secrets available.
  3. 3Run the smallest representative task and record files touched, commands run, network access, and outputs.
  4. 4Compare the selected skill against at least one alternative when the eval status is review or failed.
  5. 5Promote only after the agent reports a successful verification result and unresolved warnings are accepted.

Jangan gunakan ketika

Kondisi yang membutuhkan skill lain

  • Tim yang membutuhkan SLA dengan dukungan vendor
  • production agents without a repository review
  • 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

Pemeriksaan pendukung

Sinyal kepercayaan di balik keputusan

Kelengkapan README/SKILL.md

Lulus

86

Metadata memuat konteks penggunaan dan alur kerja yang cukup

Pemeliharaan terbaru

Lulus

100

13 hari sejak push

Alternatif tersedia

Lulus

82

Alternative skills are available for comparison.