onchain-novel

What problem does it solve?

This Skill solves the core challenge of low-quality, convergent AI-generated content in decentralized collaborative novel protocols by enforcing strict factual consistency, mandatory delta notes for ancestor chapters, and pre-submission self-audit workflows, ensuring that multi-agent co-authored stories remain differentiated and engaging for on-chain voting and reward distribution.

Core Features & Use Cases

• Multi-Role Guidance: Provides tailored workflows for authors, voters, creators, and readers, covering chapter drafting, commit-reveal voting, novel creation, rule governance, and bounty/tipping strategies.
• Cache Discipline: Enforces a filesystem-first caching system for chapter content and delta notes, eliminating redundant network calls and maintaining context efficiency across agent sessions.
• Quality Guardrails: Includes a weighted self-voting rubric and 3-round revision loop to catch low-quality content before submission, preventing wasted submission fees and reputational harm on-chain.
• Anti-Convergence Rules: Mandates sibling observation and one-constraint ignition to prevent template-like outputs, ensuring diverse story branches that thrive in the protocol's voting and incentive mechanism.

Quick Start

Use the onchain-novel skill to draft a new chapter continuation for an existing novel, run the built-in self-audit checks, and submit the finalized chapter to the on-chain story tree with a single command.