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repair-agent

Localize faults, generate patches, and validate fixes across multi-language codebases.

1|Updated Apr 23, 2026
Search Tags:#debugging#test-driven#autonomous#repair#patch-generation#fault-localization
One-click install
npx skills add https://github.com/mtsatryan/openclaw-ai-agents --skill repair-agent-mtsatryan
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: repair-agent
Source: https://github.com/mtsatryan/openclaw-ai-agents/tree/main/repair-agent
Command: npx skills add https://github.com/mtsatryan/openclaw-ai-agents --skill repair-agent-mtsatryan

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Autonomous bug fixing and iterative patching reduce time spent debugging by automatically locating faults, generating fixes, and validating results.

Core Features & Use Cases

  • Fault localization using test failures and stack traces
  • Hypothesis-driven debugging and patch generation
  • Iterative refinement with execution feedback and automatic verification
  • Multi-language support across Java, Python, JavaScript, TypeScript, Go, and Rust

Quick Start

Provide a failing codebase and test suite, then run RepairAgent to localize faults, generate patches, and validate fixes iteratively.

Frequently Asked Questions about repair-agent

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

FAQPage Schema
How do I automatically fix bugs using test failures in my codebase?▼

Yes, autonomous repair agents support multi-language stacks including Java, Python, JavaScript, TypeScript, Go, and Rust. The agent uses test-driven patch generation to localize faults and validate fixes iteratively across these languages, ensuring safe and minimal repairs.

What do I need to provide for automated fault localization and patch generation?▼

You need to provide a failing codebase, its test suite, and a defined patch validation workflow. The repair agent uses these inputs to perform fault localization, generate hypothesis-driven patches, and validate fixes iteratively through execution feedback.

What is hypothesis-driven debugging for generating code patches?▼

Hypothesis-driven debugging is an iterative process where the agent localizes faults using test failures, generates targeted patch hypotheses, and validates them against a test suite. This enables autonomous refinement to produce safe, minimal fixes across multi-language stacks.

Can I use autonomous repair for iterative refinement of failing tests?▼

Yes, autonomous repair is designed for iterative refinement of failing tests. The agent generates patches, runs execution feedback to validate the fix, and automatically refines the patch until the test suite passes, ensuring safe and minimal code repairs.

When should I not use an autonomous repair agent for patch generation?▼

You should not use an autonomous repair agent when you lack a defined patch validation workflow or failing tests. The agent requires test failures, code context, and a validation workflow to produce safe, minimal fixes; without these inputs, it cannot operate effectively.

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