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Reference document for monopoly scale-benchmarks.
Passed 24 of 26 test cases with the skill, and 13 of 26 without it.
and 13 more in the full report
11 fixed14 passed either way2 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
What document count threshold per index serves as the recommended scale trigger for re-sharding or splitting an Elasticsearch index?
| Checked | Without skill | With skill |
|---|---|---|
| Identifies 100 million documents per index as the scaling trigger. | Missed | Passed |
The instructions your model reads when the skill loads.
Requests per second (avg) = DAU × avg_requests_per_user_per_day / 86400
Requests per second (peak) = avg_RPS × peak_multiplier
Peak multipliers by app type:
Social media: 5–10×
E-commerce: 3–5× (higher during sales)
News / media: 10–20× (breaking news spike)
B2B SaaS: 2–3× (business hours spike)
Gaming: 5–15× (event-driven)
Storage per day = requests_per_day × avg_payload_size
Storage per year = storage_per_day × 365
With replication = storage_per_year × replication_factor (3× typical)
With CDN/cache = reduce by cache_hit_ratio (80% hit = 20% origin load)
Common payload sizes:
Tweet / short text: 500B
Social post with text: 2KB
Profile data: 5KB
Image (compressed): 200KB–2MB
Video (per minute): 50MB (720p), 150MB (1080p)
API JSON response: 1–20KB
Inbound bandwidth = avg_request_size × RPS
Outbound bandwidth = avg_response_size × RPS
test cases passed, vs 13 / 26 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.