Implement a Schema-Driven Execution Pipeline with Safety Guardrails

[tercel]

[Problem]
Developers lacked a unified way to define business modules that could be safely consumed by AI agents across different languages (Python/TS). Traditional function calls lacked automatic input/output validation, and there was no built-in protection against common AI-driven failures like infinite recursion or runaway execution.

[Why]
To build a reliable "AI-Perceivable" ecosystem, we need a "Contract-First" approach. Safety is paramount when an LLM is in control; without strict call depth limits and execution timeouts, a single prompt could crash the entire system or incur massive costs.

[How]

• Schema-First: Developed the @module decorator using Pydantic (Python) and JSON Schema (TS) for zero-boilerplate validation.
• Executor Pipeline: Designed a deterministic 10-step execution pipeline (later expanded) that handles validation, authentication, and middleware before the actual logic runs.
• Safety Guards: Built-in Call depth limits, Circular call detection, and Frequency throttling directly into the core engine.