error-recovery

Name: error-recovery
Availability: InStock
Author: alangeb

Analyze audit logs and retry failed API calls with exponential backoff.

Updated Jun 22, 2026

Search Tags:#debugging #audit #error #resilience #recovery #backoff

Ready to run

npx skills add https://github.com/alangeb/tau --skill error-recovery-alangeb

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: error-recovery
Source: https://github.com/alangeb/tau/tree/main/src/skills/error-recovery
Command: npx skills add https://github.com/alangeb/tau --skill error-recovery-alangeb

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This skill addresses the fragility of AI agent sessions by providing automated mechanisms to detect, analyze, and recover from tool errors, API failures, and context overflows.

Core Features & Use Cases

Error Pattern Detection: Automatically identifies recurring tool errors and API connection failures from audit logs.
Recovery Orchestration: Implements exponential backoff for API retries and provides diagnostic tools to resume crashed sessions.
Use Case: If an agent session hangs due to a context overflow or a transient API connection issue, this skill analyzes the audit log to determine the failure point and applies the appropriate recovery strategy to resume the task.

Quick Start

Run the error recovery helper on your latest audit log to identify and resolve pending tool errors.

Frequently Asked Questions about error-recovery

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

FAQPage Schema

How do I automatically recover an AI agent session from an API connection drop?▼

To automatically recover an AI agent session from an API connection drop, this skill parses audit logs to detect the failure point and applies automated exponential backoff retry logic to resume the task.

What is the best way to debug runtime failures and context window exhaustion in AI workflows?▼

Debugging runtime failures and context window exhaustion in AI workflows involves parsing session audit logs to identify error patterns, which this skill automates to help systematically restore crashed sessions.

Do I need Python 3 to run automated error recovery and backoff routines?▼

Yes, you need Python 3 and standard Unix utilities to execute the diagnostic scripts and automated backoff routines that facilitate session restoration and error recovery.

Can I detect recurring tool errors from existing audit logs?▼

Yes, you can detect recurring tool errors from existing audit logs by running the error recovery helper, which automatically identifies and analyzes recurring tool errors and API connection failures.

How does exponential backoff help resume crashed AI agent sessions?▼

Exponential backoff helps resume crashed AI agent sessions by progressively increasing the wait time between API retries, effectively managing transient connection issues and preventing server overload during recovery orchestration.