swe-bench

Diagnose GitHub issues, generate patches, and validate fixes via shell commands.

Updated Apr 18, 2026
One-click install
npx skills add https://github.com/meet1919/simple-python-agent --skill swe-bench
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: swe-bench
Source: https://github.com/meet1919/simple-python-agent/tree/main/skills/swe-bench
Command: npx skills add https://github.com/meet1919/simple-python-agent --skill swe-bench

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Software engineering issues can be diagnosed and fixed more efficiently when an autonomous agent coordinates code exploration, patching, and validation within a repository.

Core Features & Use Cases

  • Autonomous issue diagnosis and patch generation
  • Read, edit, and verify changes using a deterministic workflow
  • Use case: given a bug report in a GitHub issue, the agent rewrites a patch, applies it, and runs tests to confirm a fix

Quick Start

Describe the issue and let the agent map the codebase, inspect implicated files, apply patches with edit_file, and verify changes by running tests.

Frequently Asked Questions about swe-bench

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

FAQPage Schema
How do I autonomously patch GitHub issues from bug reports?

Autonomously patching GitHub issues involves analyzing the codebase, applying changes with edit_file, and validating fixes by running tests. The agent maps implicated files, rewrites patches, and executes shell commands to confirm the bug is resolved.

What is the workflow for autonomous software engineering issue diagnosis?

Autonomous software engineering issue diagnosis is a deterministic workflow where the agent reads repository files, identifies the root cause of a bug, proposes a code patch, and verifies the modification through lightweight checks and test execution.

How do I validate code patches by running tests in a repository?

To validate code patches by running tests, the agent applies the proposed changes using edit_file and then executes shell commands via run_bash_command. This validates that the patch resolves the issue without breaking existing repository functionality.

Can I use autonomous debugging for GitHub repository maintenance?

Yes, you can use autonomous debugging for GitHub repository maintenance. The agent inspects implicated files, applies fixes, and runs tests to ensure the software engineering issue is fully resolved within the existing codebase structure.

What's the best way to automate patch generation for software bugs?

The best way to automate patch generation for software bugs is using an autonomous agent that explores the codebase, rewrites patches, and iterates on fixes. It applies changes and runs tests to verify the patch successfully resolves the issue.

Do I need specific dependencies to run autonomous code patching tasks?

No specific dependencies are required to run autonomous code patching tasks. The agent operates autonomously using built-in shell execution, file viewing, and file editing capabilities to diagnose and resolve software engineering issues directly.