What problem does it solve?
This skill resolves the common issue where AI agents get stuck in repetitive tool call loops, hitting step count limits or maximum output token caps without producing a final, usable output, leading to failed workflows and wasted compute resources.
Core Features & Use Cases
- Loop Signature Diagnosis: Step-by-step checklist to confirm if an agent is stuck in a tool loop by analyzing session tool call patterns.
- Termination Criterion Guidance: Instructions to add explicit stop conditions to agent prompts to prevent open-ended, repetitive tool calls.
- Terminal Tool Configuration: Advice on setting up
outputTo and complete tool injection to give agents a clear exit path.
- Use Case: For example, if you have an agent tasked with triaging GitHub issues that runs 10+ repeated search queries without outputting a final report, this skill helps you adjust the prompt and configuration to get a successful result.
Quick Start
Use the debugging-tool-loops skill to diagnose and fix an agent that is stuck making repeated tool calls without producing a final response.