tbench

Automate Unix agent benchmarking with Terminal-Bench 2.0 on Docker or Daytona.

Updated Jan 28, 2026
One-click install
npx skills add https://github.com/onchainengineer/copilot-tree --skill tbench
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: tbench
Source: https://github.com/onchainengineer/copilot-tree/tree/main/.unix/skills/tbench
Command: npx skills add https://github.com/onchainengineer/copilot-tree --skill tbench

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill enables automated benchmarking and failure analysis for Unix-based agents using Terminal-Bench 2.0, providing a repeatable workflow to measure performance and identify bottlenecks.

Core Features & Use Cases

  • Unified benchmarking: Run full or partial Terminal-Bench benchmarks against Unix agents locally (Docker) or in Daytona cloud sandboxes.
  • Configurable workloads: Control datasets, concurrency, timeouts, and agent settings via environment variables (TB_DATASET, TB_CONCURRENCY, TB_TIMEOUT, TB_ENV, TB_TASK_NAMES, TB_ARGS).
  • Result tracking: Automatically collect run results, logs, and per-task outcomes for performance analysis and leaderboard submissions.
  • Use Case: A team validating agent robustness across tasks like chess moves or maze navigation by executing scripted benchmark runs and comparing results.

Quick Start

Use the tbench skill to run the full terminal benchmark suite or targeted tasks with Makefile targets and TB_ARGS.

Frequently Asked Questions about tbench

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

FAQPage Schema
How do I run Terminal-Bench benchmarks for Unix agents in a local Docker environment?

Run Terminal-Bench benchmarks for Unix agents by setting the TB_ENV variable to target a local Docker environment, then execute the suite to automatically collect per-task outcomes and logs under the runs/ directory for performance analysis.

Can I run specific Terminal-Bench tasks instead of the full benchmark suite?

Yes, run specific Terminal-Bench tasks by defining the TB_TASK_NAMES environment variable, allowing targeted benchmarking and failure analysis for specific scenarios like chess moves or maze navigation instead of executing the entire suite.

How do I configure concurrency and timeouts for Unix agent benchmarking?

Configure Unix agent benchmarking concurrency and timeouts by setting the TB_CONCURRENCY and TB_TIMEOUT environment variables, which control parallel execution limits and maximum allowed runtime per task during the Terminal-Bench evaluation.

Does Terminal-Bench support cloud sandbox environments for agent evaluation?

Terminal-Bench supports cloud sandbox environments for agent evaluation by configuring the TB_ENV variable to target Daytona cloud sandboxes, enabling remote execution of benchmark suites with configurable datasets and concurrency settings.

What is the best way to analyze agent benchmark failures collected from Terminal-Bench runs?

Analyze agent benchmark failures by reviewing the per-task outcomes and logs automatically collected under the runs/ directory after Terminal-Bench execution, then integrating with Harbor for comprehensive evaluation and leaderboard submissions.

Do I need Harbor to evaluate Terminal-Bench agent benchmark results?

Harbor integration is used for evaluation and leaderboard submissions after Terminal-Bench runs, working alongside the automatically collected run results and logs to measure Unix-based agent performance and identify bottlenecks.