agent-decision-loop-engineering

Name: agent-decision-loop-engineering
Availability: InStock
Author: agenticgogol

Defines agent control-flow loops with step ceilings, termination conditions, retries, and human interrupt points.

1|9|Updated Jul 11, 2026

Search Tags:#ai agents #agent design #langgraph #human-in-the-loop #control flow #retry policy #termination conditions

Ready to run

npx skills add https://github.com/agenticgogol/Edureka_Coding_Agent_Enabled_Demo_11Jul --skill agent-decision-loop-engineering-agenticgogol

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: agent-decision-loop-engineering
Source: https://github.com/agenticgogol/Edureka_Coding_Agent_Enabled_Demo_11Jul/tree/main/.claude/skills/agent-decision-loop-engineering
Command: npx skills add https://github.com/agenticgogol/Edureka_Coding_Agent_Enabled_Demo_11Jul --skill agent-decision-loop-engineering-agenticgogol

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Designing an AI agent without explicit loop controls leads to runaway executions, unbounded retries, and silent low-confidence answers. This Skill provides a structured rubric for deciding how an agent's execution loop terminates, retries, and pauses for human approval, producing a reviewed design document before any code is written. ## Core Features & Use Cases - Loop Rubric Interview: Asks six batched questions covering step ceilings, termination conditions, retry policy, human-in-the-loop interrupts, ceiling-exceeded behavior, and replanning caps. - Cross-Stage Validation: Verifies that every tool marked "human approval required" in stage 4 has a corresponding interrupt point in the loop design. - Design Document Output: Writes system_design/07_loop_engineering.md with a PENDING APPROVAL status and stops for explicit user sign-off. - Use Case: While designing a LangGraph-based support agent, use this Skill to set a maximum of 15 tool calls per task, define escalation on ceiling breach, and map payment-refund tools to mandatory human approval pauses. ## Quick Start Run stage 7 of the agent-system-design pipeline to decide the agent's step ceiling, termination conditions, retry policy, and human interrupt points, then approve the generated loop engineering document.

Frequently Asked Questions about agent-decision-loop-engineering

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

FAQPage Schema

How do I set a step ceiling for an AI agent loop?▼

Set a concrete maximum number of steps or tool calls based on the smallest ceiling covering the usecase's real worst case, not an arbitrary safety margin. Never leave it unbounded as "as many as needed" — even a rough estimate the user revises later is required.

How to add human-in-the-loop approval points to an agent?▼

List every tool marked "human approval required" in the earlier tool-design stage and map each one to an explicit interrupt point in the loop where execution pauses. Missing any of them is treated as a design gap that must be surfaced before finalizing.

What retry policy should an agent use for tool failures?▼

Use a small fixed retry count with backoff for transient tool failures, and a single corrected-prompt retry for malformed-output failures. Unbounded retries are explicitly discouraged because they mask persistent errors and waste budget.

Does loop engineering apply to deterministic workflows without an agent loop?▼

Yes, but minimally. If the earlier architecture stage chose deterministic code or a fixed workflow, the stage still runs and explicitly states that no dynamic loop exists, rather than being skipped entirely.

What happens when an agent hits its step ceiling without finishing?▼

The design must choose escalation to a human with partial state, an explicit "could not complete" response, or a hard fail. Silently returning a low-confidence best-effort answer as if complete is the exact failure mode this stage prevents.