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GitTaskBench: A Benchmark for Code Agents Solving Real-World Tasks Through Code Repository Leveraging

AAAI 2026 · Multi-agent systems and games › LLM agents · approach: Software engineering agent benchmarks · 3 citations (OpenAlex)

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Introduces GitTaskBench, a 54-task benchmark for code agents that must leverage GitHub repositories (including environment setup) to solve real-world multimodal tasks, plus an alpha-value metric for economic benefit, evaluated across Aider, OpenHands, and SWE-Agent with multiple LLMs.

Problem

Existing code-agent benchmarks focus on isolated code generation or program repair and rarely test whether agents can autonomously set up and repurpose open-source repositories to complete end-to-end, user-centric tasks.

Approach

A benchmark of 54 repository-grounded daily-life tasks across 7 modalities, each with human-curated automated test scripts (ECR and TPR), plus an alpha-score that nets agent success, quality, and API cost against freelance market value of the task.

Key results

Surprising findings

Limitations

Experimental setup

Datasets: GitHub repositories (18 Python projects)

Benchmarks: GitTaskBench

Metrics: Execution Completion Rate (ECR) Task Pass Rate (TPR) alpha-score token cost

Baselines: Aider SWE-Agent OpenHands

Builds on: SWE-Bench OpenHands SWE-Agent Aider

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