Documentation before drift
Architecture and behavior are documented as contracts instead of being reconstructed after implementation changes.
Qbit AI Toolkit is the versioned home for prompt-engineering guidance, AI development tooling, MCP usage, reusable agent skills, policies, templates, and the engineering contracts that connect them.
Each documentation domain has its own navigation so operational tooling, prompt design, MCP integrations, agent behavior, and engineering reference do not collapse into one mixed hierarchy.
Learn how to write explicit prompts, use reusable patterns, and evaluate behavior instead of relying on ad-hoc wording.
Setup scripts, reusable assets, Codex AI Tooling, repository-local helpers, verification, maintenance, and troubleshooting.
Configure and use Model Context Protocol integrations with explicit capability, permission, transport, and security boundaries.
Design reusable skills, publish ready-made workflows, and separate agent policies from task-specific execution logic.
Architecture, asset contracts, conventions, security boundaries, versioning, and compatibility rules for maintainers.
The first implemented catalog asset installs repository-owned AI development tooling through a versioned, cross-platform installer lifecycle with explicit ownership, verification, doctor, recovery, and uninstall behavior.
Architecture and behavior are documented as contracts instead of being reconstructed after implementation changes.
Prompts, skills, templates, installers, and policies have explicit ownership and consumer boundaries.
Operational tooling is expected to expose verification, failure behavior, and evidence—not just create files.
Use the top navigation to move between learning material, operational tooling, integrations, reusable agent behavior, and engineering reference.