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Qdrant

Qdrant

qdrant.techVector DatabasesOpenCodeOpenCode
89/ 100
B
Score Breakdown89%

Lost points on 3 checks

  • time9/15
  • efficiency6/10
  • zero errors0/5
Eval Score (70% weight)85%
cost$0.01 (<$0.05, excellent)+10
time45s (30s–60s, great)+9
efficiency8 tool calls (≤10, great)+6
found docsTouched docs at qdrant.tech: yes (2 matching tool calls)+10
zero errorsTool outputs with errors/tracebacks: 2+0
syntax validCode compiles/parses correctly+5
created filesGenerated files: 2 (need ≥1)+10
full executionMethod: full_execution, Exit: 0+35
Checklist Score (30% weight)100%
Context7
Link+14
llms.txt
Link+14
MCP Server
Link+14
Typed SDK
Link+14
OpenAPI
Link+14
Agent Skills
Link+14
CLI
Link+14

Checklist determined by AI. If something looks wrong, .

Final Score
A: >=90%B: 75-89%C: 55-74%D: <55%
(85 × 0.7) + (100 × 0.3)= 89%
Replay
Using https://qdrant.tech/documentation, complete the following task:

Using Qdrant, build me a FAQ search system:

1. Store these 3 FAQs:
   - Q: "How do I reset my password?" A: "Go to Settings > Security > Reset Password"
   - Q: "How do I cancel my subscription?" A: "Go to Settings > Billing > Cancel Plan"
   - Q: "How do I update my email?" A: "Go to Settings > Profile > Edit Email"

2. Search for: "I can't log into my account"

3. Print the best matching FAQ and its similarity score
faq_search.py

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See Qdrant's score trend, layer rankings, and competitive position.

Run completed Oct 23, 2026, 7:06 AM