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XPRNetwork
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creative

Generate and store AI creative deliverables in IPFS or GitHub repositories.

3|3|Updated Feb 5, 2026
Search Tags:#github#ai#creative#image-generation#deliverables#pdf-generation#ipfs
One-click install
npx skills add https://github.com/XPRNetwork/xpr-agents --skill creative
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: creative
Source: https://github.com/XPRNetwork/xpr-agents/tree/main/openclaw/starter/agent/skills/creative
Command: npx skills add https://github.com/XPRNetwork/xpr-agents --skill creative

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This set of creative tools enables AI agents to produce, package, and securely store deliverables for jobs—covering media, documents, and code artifacts—so results can be shared or on-chained with verifiable provenance.

Core Features & Use Cases

  • Store deliverables in IPFS or as data URIs for flexible delivery workflows.
  • Generate media (image, video) and PDFs from Markdown, with automatic embedding of assets and optional GitHub repository creation for code deliverables.
  • Create GitHub repositories to host deliverables and provide transparent, reviewable artifacts for jobs.
  • Use cases include producing client-ready creative assets, project documentation, and artifact packaging for on-chain or off-chain delivery.

Quick Start

Store a Markdown deliverable for a job, then call xpr_deliver_job to complete the delivery.

Frequently Asked Questions about creative

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

FAQPage Schema
How do I automate image and video generation for client deliverables?▼

Automate image and video generation by using tools that produce media assets and package them for delivery. This process generates creative assets and stores them in IPFS or as data URIs for flexible, client-ready sharing.

Can I generate PDFs from Markdown and store them on IPFS?▼

Yes, you can generate PDFs from Markdown with automatic asset embedding and store them on IPFS. This workflow packages documents for secure delivery with verifiable provenance for on-chain or off-chain sharing.

What is the best way to package code artifacts and project documentation for jobs?▼

Package code artifacts and documentation by creating GitHub repositories to host deliverables. This approach provides transparent, reviewable artifacts and securely stores project outputs with verifiable provenance.

Does this workflow support creating GitHub repositories for AI-generated code deliverables?▼

Yes, it supports creating GitHub repositories to host code deliverables. This provides transparent, reviewable artifacts for jobs and securely stores media, documents, and code outputs for on-chain or off-chain delivery.

How do I securely store and share AI-generated media with verifiable provenance?▼

Securely store and share AI-generated media by uploading assets to IPFS or saving them as data URIs. This mechanism ensures flexible delivery workflows and verifiable provenance for client-ready creative assets.

What are the limitations of using data URIs versus IPFS for creative deliverable storage?▼

Using data URIs embeds assets directly for self-contained delivery, while IPFS provides decentralized storage for verifiable provenance. Data URIs may increase file size, whereas IPFS requires network access for retrieval.

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