proof-generator

Generate a ProofBundle with zkTLS and TDX attestations for worker-fetched data.

5|Updated Mar 11, 2026

Search Tags:#data provenance #attestation #proof generation #zkTLS #Intel TDX #C2C #worker agent

Ready to run

npx skills add https://github.com/Skottbie/VeriTask --skill proof-generator

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: proof-generator
Source: https://github.com/Skottbie/VeriTask/tree/main/worker_node/skills/proof-generator
Command: npx skills add https://github.com/Skottbie/VeriTask --skill proof-generator

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires @reclaimprotocol/zk-fetch, dstack-sdk, and includes scripts (resource) components.

What problem does it solve?

This Skill addresses the critical need for verifiable data provenance and execution integrity in automated workflows, ensuring trust and security in data transactions between AI agents.

Core Features & Use Cases

Dual-Layer Proof Generation: Creates cryptographic attestations using both Reclaim's zkTLS for data provenance and Phala's Intel TDX TEE for execution environment integrity.
Automated Data Verification: Integrates seamlessly into Claw-to-Claw (C2C) flows, providing verifiable credentials for data fetched by worker agents.
Use Case: When an AI client needs to outsource a data scraping task, this skill on the worker agent will fetch the data, wrap it in a zkTLS proof and a TDX attestation, and return a ProofBundle for the client to verify and act upon.

Quick Start

Use the proof-generator skill to generate a ProofBundle for the 'aave' protocol.

Frequently Asked Questions about proof-generator

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate verifiable data proofs for AI agent workflows?▼

You generate verifiable data proofs by wrapping fetched data in a ProofBundle that combines Reclaim Protocol zkTLS for data provenance and Intel TDX TEE for execution integrity. This dual-layer approach ensures trust in cross-agent data procurement pipelines.

What is zkTLS and TEE attestation used for in data provenance?▼

zkTLS and TEE attestation verify data origin and execution environment integrity. zkTLS proves where data came from cryptographically, while Intel TDX TEE attests that the worker agent processed the fetched data securely without tampering.

How do I verify data fetched by a worker agent in C2C pipelines?▼

You verify data in Claw-to-Claw pipelines by having the worker agent generate a ProofBundle containing verifiable credentials. The client agent then validates this bundle to confirm both the origin and secure processing of the outsourced data.

Do I need Reclaim Protocol and dstack-sdk to generate a ProofBundle?▼

Yes, generating a ProofBundle requires both the Reclaim Protocol zk-fetch and dstack-sdk dependencies. Reclaim handles data provenance proofs, while dstack provides the Intel TDX TEE attestation for execution environment integrity.

Can I use this proof generation skill for automated data scraping verification?▼

Yes, this skill is designed for automated data scraping verification. When an AI client outsources scraping tasks, the worker agent fetches data, wraps it in cryptographic proofs, and returns a verifiable bundle for the client.

What's the difference between zkTLS and Intel TDX for proof generation?▼

zkTLS focuses on data provenance by proving the origin of fetched data, while Intel TDX TEE focuses on execution integrity by proving the processing environment was secure. Combining both creates a dual-layer verification system for complete trust.