OpenKol is a verification layer. If it isn’t consistent, it isn’t useful. Reliability comes from three things:Documentation Index
Fetch the complete documentation index at: https://docs.openkol.net/llms.txt
Use this file to discover all available pages before exploring further.
- deterministic scoring,
- predictable data handling, and
- transparent behavior when inputs are missing.
Deterministic scoring
Scores are computed from normalized inputs using pure functions.- same post + same timestamp + same market data ⇒ same result
- score components are capped/clamped so one metric can’t dominate everything
- the scoring system is documented so users can understand what drove the result
Operational reliability
OpenKol is designed for real-world usage:- caching around expensive lookups (posts, candles, analysis snapshots)
- persistence of analysis snapshots so permalinks remain stable
- health checks and guardrails to avoid partial or misleading results
User trust
Trust is earned by being explicit:- OpenKol uses public data (social metadata + market data)
- results are reproducible and shareable
- limitations and edge cases are acknowledged rather than hidden