intent-author

Publish structured intents to the Convergent intent graph using the IntentNode schema.

4|1|Updated Jan 27, 2026

Search Tags:#validation #schema #ai agents #intent authoring #convergent #intent graph

Ready to run

npx skills add https://github.com/AreteDriver/ai-skills --skill intent-author

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: intent-author
Source: https://github.com/AreteDriver/ai-skills/tree/main/agents/analysis/intent-author
Command: npx skills add https://github.com/AreteDriver/ai-skills --skill intent-author

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and scripts (resource) components.

What problem does it solve?

This Skill ensures that AI agents publish clear, machine-comparable, and honest intents to the Convergent intent graph, preventing chaos and enabling effective coordination.

Core Features & Use Cases

Intent Authoring: Guides agents in creating well-structured intent nodes with specific actions, categories, provides/requires lists, constraints, and stability scores.
Validation: Enforces a strict quality checklist to ensure intents are specific, verifiable, and honest.
Use Case: An agent needs to define a new User model for an authentication module. This Skill helps the agent author an interface intent, specifying the model's fields, constraints (like email uniqueness), and stability score, ensuring other agents can reliably use it.

Quick Start

Use the intent-author skill to author a new intent for creating a User model with specific fields and constraints.

Frequently Asked Questions about intent-author

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

FAQPage Schema

What is an intent graph in AI agent coordination and when do I need it?▼

An intent graph enables AI agents to publish clear, machine-comparable, and honest intents for effective coordination. You need it when agents must define decisions, interfaces, dependencies, or constraints within the Convergent ecosystem.

How do I author high-quality AI intents for Convergent?▼

To author AI intents for Convergent, create well-structured intent nodes specifying actions, categories, provides/requires lists, constraints, and stability scores, adhering strictly to the defined IntentNode schema and quality checklist.

How does intent validation ensure machine comparability for AI agents?▼

Intent validation enforces a strict quality checklist ensuring intents are specific, verifiable, and honest. This requires adherence to a defined IntentNode schema and stability scoring guide, guaranteeing machine comparability and honest representation of commitment.

Can I use intent authoring to define data models and dependencies for AI agents?▼

Yes, intent authoring supports defining new data models like a User model for authentication modules. Agents can specify fields, constraints such as email uniqueness, and stability scores, ensuring other agents can reliably use the interface.

What are the limitations of authoring intents without a schema for AI agents?▼

Without a schema, AI agent intent publishing risks creating unclear, non-machine-comparable, and dishonest intents, preventing effective coordination and causing chaos within the Convergent ecosystem. Strict schema adherence prevents this.