agentic-layer

What problem does it solve?

It helps teams avoid brittle, UI-centric interfaces by defining clear, machine-readable contracts that agents can reliably call and interpret.

Core Features & Use Cases

• JSON-first interfaces: Prefer structured data over HTML-like visual outputs so agents can consume responses deterministically.
• Named operations for actions: Represent capabilities as explicit, callable operations rather than implicit UI interactions.
• Machine-readable state and feedback: Model state as a document that can be validated, routed, and used across steps, with structured results and self-describing capabilities.
• Use Case: When building an autonomous product workflow (e.g., repo analysis or engineering planning), use this skill to define the agent’s human-visible and agent-visible interfaces so the agent can execute actions safely and interpret outputs consistently.

Quick Start

Ask the AI to design your product’s agentic layer by listing the agent JSON input/output schema, naming the operations, defining a machine-readable state document, and specifying a capabilities endpoint.