👣VRS

Verifiable Reputation Score (VRS): A Coverage-Penalized Multi-Source Reputation Scoring Framework

Purpose & Vision

The Verifiable Reputation Score (VRS) was first introduced as a proof-based mechanism to recognize authenticity, contribution, and engagement across the zkPass ecosystem. It quantifies how complete and credible your digital identity is across multiple verified data sources, while preserving privacy through zero-knowledge proofs. Higher scores grant greater access and priority in ecosystem participation, ensuring that credibility and genuine contribution are rewarded alongside timing.

Quick Start

Access the VRS module at portal.zkpass.org, where users can connect wallets, verify data sources, and view their computed Verifiable Reputation Score in real time.

What you get

A personal VRS ranging from 0 to 100 determines your $ZKP allocation priority on Kaito Capital Launchpad. Users with higher scores receive preferential access to allocations under the campaign rules.

What you need

1. A wallet such as MetaMask.

2. TransGate on your device. • Desktop Chrome installs the TransGate extension. • iOS uses TransGate via app-clip. No need to download any apps. • Android installs the TransGate app from Google Play.

3. A few eligible accounts to verify such as Binance, LinkedIn, GitHub, Duolingo, or Kaito Yap.

We recommend using the desktop web version for the smoothest experience.

How to verify on desktop web

1. Install the TransGate Chrome extension.

2. Open the zkPass Portal page.

3. Connect your X account → Pick a source and select Verify → A new tab opens the source site → Sign in as usual.

4. Click Start in the popup, a zero-knowledge proof generates locally within seconds. Your VRS updates automatically. No gas fee is required.

How to verify on mobile

iOS

1. Open the zkPass Portal page in the in-app browser flow.

2. Connect your X account and sign in to each source when prompted and tap Start.

3. Return to see the Verified status and updated VRS.

Android

1. Install TransGate from Google Play.

2. Open the zkPass Portal page in any wallet.

3. Connect your X account, sign in to a source, tap Start, then return to view the updated VRS.

Privacy and security

Proofs are generated locally. Raw personal data does not leave your device. Verifiers receive only cryptographic attestations.

Core Principal

VRS isn’t about popularity, wealth, or social ranking. It’s about proof density - how many aspects of your digital footprint have been independently verified, and how consistent they are.

• A single Binance KYC attestation may prove you’re a real person.

• A LinkedIn or GitHub profile shows professional authenticity.

• A Duolingo streak or Kaito YAP credential reflects learning or contribution.

Together, these form your verifiable identity fabric. The more complete and trustworthy that fabric becomes, the higher your VRS.

Conceptual Design

The VRS is derived from zkPass’s open-source Coverage-Penalized Multi-Source Reputation Framework, designed to fairly evaluate users based on both what they’ve proven and what they’ve yet to prove.

It consists of five layers:

Layer	Purpose	What It Does
Feature Normalization	Handle raw metrics (e.g., followers, balances, account age)	Map heterogeneous data to 0–1 range using log scale, SoftClip, and Boolean mapping A Coverage-Penalized Multi-Sour…
Per-Source Aggregation	Combine features within one source	Weighted sum based on feature importance
Cross-Source Weighting	Aggregate scores from multiple sources	Assign global weights (e.g., KYC > Social) without re-normalizing missing sources
Weighted Coverage	Compute how complete your proofs are	Evaluate coverage ratio across all expected sources
Nonlinear Penalty	Apply soft discount for missing data	Use exponent α > 1 to intensify incompleteness penalty

Mathematical Formulation

Let Si​ be the score of source i, and Wi​ its global weight. Let A be the set of sources a user has verified.

$$(1) Raw Aggregation:Rraw=∑i∈AWiSi$$

$$(2) Coverage Ratio:C=∑i∈AWi∑iWi$$

$$(3) Final Score with Penalty:VRS=100×Rraw×Cα$$

Where α>1 controls how aggressively incomplete coverage reduces your score. Example: with C=0.8,α=1.5, only 83.7 % of the value is retained

Score Interpretation

Score	Meaning	Typical Profile
0–30	Limited Proof	Only 1–2 basic verifications
30–60	Partial Identity	Some key proofs (KYC + social account)
60–80	Verified User	Multiple dimensions covered
80–90	High Credibility	Strong proofs with minor gaps
90–100	Fully Verifiable Identity	Complete and consistent proof set

Examples

Connected Proofs	Coverage Ratio C	Approx. VRS
Twitter + Duolingo	0.4	≈ 45
Binance KYC + LinkedIn	0.6	≈ 70
Binance + OKX + LinkedIn + GitHub	0.8	≈ 85
Binance + OKX + LinkedIn + GitHub + Duolingo	1.0	≈ 95–100

Properties

• Boundedness: All scores strictly within [0, 100].

• Monotonicity: Adding new proofs or improving quality never lowers VRS.

• Weighted Fairness: High-impact sources (KYC, verified identity) carry greater influence.

• Coverage Sensitivity: Missing major sources penalized more than minor ones.

• Nonlinear Incentivization: Penalty strength tuned by α to motivate completeness.

• Interpretability: Every layer (feature → source → aggregate → coverage) is auditable.

• Extensibility: Supports temporal decay, confidence weighting, or residual mixing without breaking consistency.

How to Increase Your VRS

1. Connect More Core Proofs - Verify across financial, social, and skill dimensions.

2. Maintain Account Quality - Older, active, verified accounts score higher.

3. Diversify Your Sources - Cover both Web2 and Web3 identities.

4. Stay Consistent - VRS updates as your proof ecosystem evolves.

Algorithmic Implementation (Pseudocode)

def compute_vrs(sources, alpha=1.5):
    """
    sources: list of dicts with fields {weight, score, provided}
    """
    total_weight = sum(s["weight"] for s in sources)
    provided = [s for s in sources if s["provided"]]
    coverage = sum(s["weight"] for s in provided) / total_weight
    quality = sum(s["weight"] * s["score"] for s in provided)
    vrs = 100 * quality * (coverage ** alpha)
    return round(vrs, 2)

Open Framework & Future Extensions

The VRS framework is open for developers and projects to integrate. Future modules may include:

• Temporal Decay: recent proofs weighted higher.

• Confidence Scores: sources with cryptographic attestations weighted more.

• Federated Aggregation: cross-domain proof composition without data sharing.

By aligning economic incentives with verifiable identity strength, VRS lays the foundation for the Proof Economy - where reputation becomes a liquid, portable, and provable asset.

Open Access & Disclaimer

The Verifiable Reputation Score (VRS) framework is open and transparent by design. All algorithms, weight parameters, and pseudocode are publicly auditable and available for developers to reference or extend. The open-source implementation is maintained on GitHub: 👉 https://github.com/zkPassOfficial/Verifiable-Reputation-Score

All calculations are performed client-side; no personal or raw data leaves the user’s device. zkPass does not store, collect, or process any private information related to VRS computation. The framework is intended for informational and research purposes and should not be interpreted as a financial or investment rating.