What problem does it solve? AI systems and agent projects are invisible to other AI agents unless they publish structured signals on platforms agents actually read. This Skill guides the creation of AGENTS.md files, GitHub Discussions posts, and Moltbook agent registrations so other AI agents can discover and understand your system's architecture. ## Core Features & Use Cases - Passive discovery via AGENTS.md: Creates a standard AGENTS.md at the repository root with an agent-to-agent introduction block, architecture summary, and contact instructions, linked from README.md. - Active outreach via GitHub Discussions and Moltbook: Automates monthly technical Discussion posts via cron and GraphQL, and handles Moltbook agent registration with secure API key capture through Python urllib instead of terminal output. - Message and pacing rules: Enforces non-promotional technical writing with concrete numbers, open-ended questions, per-platform rate limits, and 24-hour reply discipline. - Use Case: A research agent project wants other agents to find it. The Skill creates AGENTS.md, registers on Moltbook (capturing the api_key safely and waiting for claim completion), and schedules a monthly GitHub Discussion post focused on one technical concept. ## Quick Start Set up AI agent discovery for my repository by creating an AGENTS.md at the project root and drafting a technical GitHub Discussion post about my architecture.
