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error-troubleshooting

Diagnose and resolve common errors in AI red teaming workflows.

11|1|Updated May 4, 2026
Search Tags:#error troubleshooting#model errors#airt#ai red teaming#attack workflow#transform errors#execution errors
One-click install
npx skills add https://github.com/dreadnode/capabilities --skill error-troubleshooting-dreadnode
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: error-troubleshooting
Source: https://github.com/dreadnode/capabilities/tree/main/capabilities/ai-red-teaming/skills/error-troubleshooting
Command: npx skills add https://github.com/dreadnode/capabilities --skill error-troubleshooting-dreadnode

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates the frustration of stalled AI red teaming (AIRT) workflows by providing clear, actionable fixes for common errors encountered during attack generation, execution, and results collection, saving you hours of debugging time.

Core Features & Use Cases

  • Comprehensive Error Coverage: Addresses model provider issues, transform configuration mistakes, category attack parsing errors, scorer misconfigurations, execution timeouts, agentic attack failures, and results collection problems.
  • Actionable Fixes: Each error entry includes a clear cause and step-by-step resolution, plus a retry strategy for persistent failures.
  • Use Case: If you receive a "Rate limit exceeded" error when running an attack against a target model, this Skill guides you to reduce iteration counts or switch to a less rate-limited provider to get your workflow running again.

Quick Start

Use the error-troubleshooting skill to diagnose and resolve the "Context length exceeded" error you are seeing when executing your AIRT attack workflow.

Frequently Asked Questions about error-troubleshooting

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

FAQPage Schema
How do I fix AIRT attack workflow errors without manual debugging?▼

To fix AIRT attack workflow errors, diagnose common issues like model provider rate limits, transform configuration mistakes, and execution timeouts using actionable resolution steps. This provides specific retry strategies to restore workflow functionality.

Why does my AI red teaming attack fail with a rate limit exceeded error?▼

AI red teaming attacks fail with rate limit exceeded errors when model providers restrict request frequency. Resolve this by reducing iteration counts or switching to a less rate-limited provider to resume attack execution.

What causes category attack parsing errors during AI red teaming execution?▼

Category attack parsing errors during AI red teaming execution stem from transform configuration mistakes or scorer misconfigurations. Applying targeted configuration corrections resolves these execution failures and restores the attack workflow.

How do I resolve agentic attack failures and execution timeouts in AIRT workflows?▼

Resolve agentic attack failures and execution timeouts in AIRT workflows by applying provided step-by-step fixes for misconfigurations. Implement retry strategies for persistent failures to successfully complete attack generation.

Can I fix model provider authentication issues during AIRT results collection?▼

You can fix model provider authentication issues during AIRT results collection by following diagnostic steps for common error scenarios. This addresses collection problems and execution failures to restore workflow functionality.

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