qdrant-scaling — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited qdrant-scaling (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Route first, then answer. Match the user's symptom in the table, Read that file, and answer from it. Do not answer from this page alone: it contains routing only, not the guidance. If two rows match, read both.
| The user says | Read |
|---|---|
| Data does not fit on a single node, running out of disk or memory as the dataset grows | scaling-data-volume/SKILL.md |
| Need to shard the collection across more nodes, data outgrew one node | scaling-data-volume/SKILL.md |
| Cannot handle enough parallel queries, need higher QPS or throughput | scaling-qps/SKILL.md |
| Can't hold the request rate, CPU is pegged | scaling-qps/SKILL.md |
| A single query is too slow, need to cut the tail latency of individual requests | minimize-latency/SKILL.md |
| p99 or tail latency too high, but traffic/QPS is fine | minimize-latency/SKILL.md |
| Queries return very large result sets and slow down | scaling-query-volume/SKILL.md |
Large limit, top-1000 queries, pagination, scroll across shards | scaling-query-volume/SKILL.md |
| Many tenants or customers, one collection each, tenant isolation | scaling-data-volume/tenant-scaling/SKILL.md |
| Only recent data matters, retention, expiring old vectors, time-based rotation | scaling-data-volume/sliding-time-window/SKILL.md |
| Single node no longer fits the workload, before deciding to shard | scaling-data-volume/vertical-scaling/SKILL.md |
| Already vertically maxed out, need more nodes, resharding | scaling-data-volume/horizontal-scaling/SKILL.md |
Latency and throughput pull opposite ways on segment count. For latency, increase segments toward the CPU core count (default_segment_number: 16). For throughput, use fewer and larger segments (default_segment_number: 2). Applying the wrong direction makes the reported problem worse.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.