When does the skill stop trying to recover?

The skill escalates to human intervention when it encounters 'Unrecoverable' errors (like Out of Memory or Disk Full) or when the defined retry limits for a specific error have been exceeded.

How does Error Recoverer decide which strategy to use?

It uses an internal classifier to determine the error category and severity, then queries causal memory for similar past issues to select strategies like 'Retry', 'Rollback', or 'Fix and Retry'.

What types of errors can Error Recoverer handle?

The skill handles a wide range of errors including transient network timeouts, resource permission issues, syntax/parsing errors, logic test failures, and environment dependency mismatches.

Can this skill automatically fix broken code?

Yes, for syntax and specific logic errors, Error Recoverer can trigger a 'Fix and Retry' workflow that attempts to debug and resolve the code issue before continuing.

Error Recoverer

Name: Error Recoverer
Author: adaptationio

byadaptationio

Seguridad y Pruebas

Automates error detection, classification, and recovery to maintain continuous and resilient autonomous coding sessions.

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The Error Recoverer skill provides Claude with a sophisticated framework for identifying and resolving issues that occur during autonomous development tasks. By classifying errors into specific categories such as transient, resource, syntax, or logic, it intelligently selects the optimal recovery strategy—ranging from exponential backoffs and state rollbacks to automated code fixes. This skill is essential for maintaining session continuity, reducing manual intervention, and ensuring that coding agents can autonomously navigate through failures by leveraging causal memory and integrated checkpoint management.

Características Principales

Multi-tier recovery strategies including exponential backoff, state rollback, and fix-and-retry
Detailed escalation protocols that generate comprehensive reports for human intervention
Intelligent error classification across transient, resource, syntax, logic, and environment categories
Automated checkpoint management for safe state restoration after unrecoverable failures
Causal memory integration to query and store successful error-to-solution chains
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Casos de Uso

Managing transient network timeouts and rate limits during complex API integrations
Automatically correcting syntax or JSON parsing errors generated during autonomous code creation
Restoring stable project states when logic changes lead to regression test failures

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Características Principales

Multi-tier recovery strategies including exponential backoff, state rollback, and fix-and-retry
Detailed escalation protocols that generate comprehensive reports for human intervention
Intelligent error classification across transient, resource, syntax, logic, and environment categories
Automated checkpoint management for safe state restoration after unrecoverable failures
Causal memory integration to query and store successful error-to-solution chains
0 GitHub stars

Casos de Uso

Managing transient network timeouts and rate limits during complex API integrations
Automatically correcting syntax or JSON parsing errors generated during autonomous code creation
Restoring stable project states when logic changes lead to regression test failures