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OpenKol turns a single public KOL post into verifiable receipts.
  • One URL in → one analysis out.
  • A deterministic scorecard combining social engagement quality and post-call market performance.
  • A simple medal grade for fast filtering.
  • A shareable permalink / OG card so results can travel.
OpenKol is built for three kinds of users:
  • Apers who want faster signal and fewer traps
  • KOLs who want proof (and a reputation that compounds)
  • Teams & builders who want measurable, comparable influencer impact
Not financial advice. This is a verification layer.

Abstract

Crypto social is fast, but verification is slow. OpenKol is a transparent verification layer for crypto KOL calls. It converts a single public post into a repeatable, data-backed scorecard that combines social engagement quality with on-chain price performance. The output is shareable, reproducible, and designed to reduce hindsight, cherry picking, and “selective time window” narratives.

The problem

Crypto social is noisy:
  • Calls are easy to publish and easy to exaggerate after the fact.
  • Screenshots, selective timestamps, and cherry-picked windows distort reality.
  • Followers waste time and capital chasing hype that doesn’t hold.
  • Teams and builders struggle to quantify the real impact of influencer reach.
In short: there is no consistent standard for “did this call actually perform?”

The OpenKol solution

OpenKol converts hype into measurable outcomes:
  • Timestamped verification: every call is anchored to a specific moment.
  • Deterministic scoring: transparent inputs, consistent outputs.
  • Two-signal model: social signal quality + post-call market performance.
  • Fast filtering: medals and scores make comparisons quick.
  • Shareable receipts: analysis pages and social cards are built to be shared.

Product overview

A single analysis produces:
  • Social score, Chart score, and Overall score (0–100)
  • A medal grade (Gold, Silver, Bronze, Red)
  • A price chart and key price stats around the call
  • A KOL profile snapshot based on tracked call history
The goal is not to predict the future. The goal is to make past performance verifiable and comparable.

Workflow (end to end)

  1. A user pastes a public post URL into the app.
  2. OpenKol normalizes post metadata (author, time, engagement, text).
  3. The text is scanned for tickers or contract addresses.
  4. If multiple symbols are detected, the user selects the intended one.
  5. Market data is pulled for the token pair around the call time.
  6. Candles are trimmed to a consistent analysis window per resolution.
  7. Social and chart scoring run as deterministic functions.
  8. The app renders an analysis dashboard and shareable social card.
  9. The analysis is cached and stored for fast reopens and long-lived shareability.

Scoring: transparent by design

OpenKol publishes its scoring logic so users can trust the output.

Social score (0–100)

Social score is derived from engagement quality relative to the author’s baseline, using signals such as:
  • Views, likes, reposts, replies, bookmarks
  • Comment quality filters (de-duplication and low-effort detection)
  • Weighted comment impact based on unique commenters
Interpretation: Social score answers “Did this call attract credible attention?” not “Was it loud?”

Chart score (0–100)

Chart score is derived from market action after the call, using signals such as:
  • Pump strength (15m spike and 1h ROI)
  • Durability (time above key thresholds in the first 6h)
  • Stability (drawdowns at 1h and 24h)
  • Liquidity health
Interpretation: Chart score answers “Did the market actually follow through?”

Overall score and medal

Overall score blends chart and social signals:
  • Overall = 70% Chart + 30% Social
Medal tiers:
  • Gold: Overall ≥ 80 AND Chart ≥ 70
  • Silver: Overall ≥ 60
  • Bronze: Overall ≥ 40
  • Red: Overall < 40
How to use this in practice
  • High Social + Low Chart → hype risk (attention without outcome)
  • Low Social + High Chart → quiet/early call that still performed
  • High Social + High Chart → strong signal + strong follow-through
  • Low Social + Low Chart → noise

KOL profile score

KOL profiles aggregate call history into a 0–100 score, designed to summarize performance and risk at a glance:
  • Performance (0–40): average outcomes and medal balance
  • Risk (0–20): drawdown profile and red rate
  • Track record (0–20): depth and recent activity
  • Influence (0–10): reach and listing signals
  • Legitimacy (0–10): account age, ratio signals, verification
Tier mapping:
  • S: 85+
  • A: 70+
  • B: 55+
  • C: 40+
  • D: below 40

Architecture and data flow

OpenKol runs as a single Next.js app with internal API routes.

Data sources

  • Public post metadata from social platforms
  • On-chain market data from a DEX analytics provider

Storage and caching

  • Postgres stores normalized posts and analysis snapshots
  • Redis caches post details, analysis results, and candle data
  • Browser local storage tracks lightweight analysis history

Rendering and shareability

  • OG images are generated on demand for shareable links
  • Analysis pages are renderable for SEO and previews

Reliability and integrity

OpenKol is built to stay reliable and fair with clear, deterministic scoring and operational safeguards. The target outcome is consistency: the same inputs should yield the same results, and users should be able to understand what drove a score.

Business model

Planned revenue model:
  • Freemium tier with a daily lookup cap
  • Pro subscriptions for higher limits and deeper history
  • Team plans for projects, agencies, and DAOs
  • API access for developers and data partners

Roadmap

Near term

  • KOL profile pages with feeds and rolling metrics
  • Leaderboards with filters and minimum call thresholds

Mid term

  • Expanded multi-chain support and richer risk flags
  • Public discovery pages for top performers

If OpenKol has (or plans) a token, the docs should include a dedicated, concrete section here. Fill this in with real numbers and rules (no vibes):
  • Token utility (what you must hold/pay/stake it for)
  • Supply, emissions, and distribution
  • Vesting schedules and unlock timeline
  • Value accrual mechanism (if any): fees, buybacks, burns, etc.
  • Governance scope (what token holders can actually change)
  • Risk disclosures
If you don’t want to promise token mechanics yet, keep this as “Coming soon” but avoid ambiguity.

Why trust OpenKol

OpenKol is built around transparency and reproducibility:
  • Every score starts from a public post and market data
  • Scoring is deterministic and documented
  • Results are designed to resist hindsight and cherry picking
If you want a faster, more credible way to filter KOLs and verify calls, OpenKol gives you the evidence.

Limitations (add this for credibility)

No scoring system is perfect. OpenKol scores what can be measured from public post metadata and market data around a timestamp. Edge cases can exist (e.g., deleted posts, unclear tickers, abnormal market conditions, thin liquidity). OpenKol is intended to improve verification—not replace judgment.