A deterministic trust-scoring engine that converts onchain activity and social signals into explainable credibility scores.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install gwap-score-protocol
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install gwap-score-protocol using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is GwapScore Protocol Core?
The GwapScore Protocol Core is a specialized framework designed to operate as a high-integrity trust management layer for decentralized ecosystems. By leveraging Openclaw Skills, this tool converts raw onchain evidence, counterparty outcomes, and social signals into canonical attestations. The core focus is on preserving explainability and removing the guesswork often associated with reputation systems. It provides a structured environment for developers to build credit systems, marketplace reputations, or partner gating mechanisms without relying on vanity metrics like follower counts or token wealth.
Built for developers who demand transparency, the protocol ensures that every score movement is backed by a verifiable reason trail. By integrating this into Openclaw Skills, agents can act as objective auditors and operators, managing the lifecycle of trust from initial classification to dispute resolution and score recalculation.
GwapScore Protocol Core Use Cases
- Scoring and reviewing wallets, merchants, or creators based on behavioral history.
- Defining trust-scoring rules, confidence logic, and decay rates for protocol-native events.
- Designing partner integrations for score-impacting events and feature-gating thresholds.
- Generating explainable audit trails for why a specific trust score changed over time.
- Mapping legacy reputation thresholds to the standardized GwapScore framework.
How GwapScore Protocol Core Works
- Subject Classification: The agent identifies the entity type, such as a borrower, merchant, or individual wallet.
- Evidence Ingestion: Raw onchain data and platform signals are organized into structured categories.
- Canonicalization: Source-specific inputs are translated into standardized GwapScore events.
- Attestation Creation: Protocol rules are applied to transform events into official attestations.
- Score Calculation: A deterministic model calculates the final score (300–900) factoring in drivers, caps, and confidence levels.
- Explanation: The system generates a comprehensive output including score bands, confidence levels, and recommended next steps.
- Recalculation: When new evidence is presented, the agent compares old and new attestations to preserve a reason trail.
GwapScore Protocol Core Setup
To deploy this skill within your Openclaw Skills environment, ensure your local directory includes the required reference and template files:
# Initialize the protocol structure
mkdir -p references templates assets/example-payloads
# Configure the scoring model reference
touch references/scoring-model-v1.md
# Set up the canonical event schema
touch references/canonical-event-schema.md
Once the files are in place, the AI agent can use Openclaw Skills to access the templates/score-output-template.md for generating standardized trust reports.
GwapScore Protocol Core Data Schema & Taxonomy
The protocol utilizes a standardized scoring and confidence framework to ensure cross-platform compatibility:
| Score Band | Classification | Description |
|---|---|---|
| 300–449 | High Risk | Low trust with significant negative signals |
| 450–599 | Emerging | Limited evidence or new accounts |
| 600–699 | Stable | Moderate trust and consistent behavior |
| 700–799 | Strong | High trust with verified outcomes |
| 800–900 | Exceptional | Verified reliability and top-tier standing |
Metadata includes confidence levels (Low, Moderate, High, Very High) which are tracked independently from the numerical score to highlight evidence density.
GwapScore Protocol Core Advanced Features
- Sybil clustering and circular transaction pattern detection for automated risk escalation.
- Automated decay and recovery rules to ensure trust scores reflect recent behavior.
- Multi-agent support for partner webhooks and cross-protocol trust events.
- Deterministic dispute resolution flows for score reversals and recalculation requests.
- Feature-gating thresholds to programmatically limit access based on score bands.
SKILL.md
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