eval-harness

Compare two variants in parallel with a model grader and structured report.

4|Updated Jan 9, 2026
One-click install
npx skills add https://github.com/baleen37/bstack --skill eval-harness-baleen37
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: eval-harness
Source: https://github.com/baleen37/bstack/tree/main/plugins/me/skills/eval-harness
Command: npx skills add https://github.com/baleen37/bstack --skill eval-harness-baleen37

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Streamlines and standardizes variant comparisons by running two options in parallel and using a model-based grader to produce an objective, comparable assessment.

Core Features & Use Cases

  • Parallel variant execution with two subagents and a single evaluation pass.
  • Supports variant types: code, llm, command, and custom workflows with a unified input specification (TASK, VARIANT_A, VARIANT_B, INPUTS, Evals).
  • Generates a structured report including per-criterion verdicts and an overall winner or tie, with anonymization for fair judging.

Quick Start

Provide a task and two variants with inputs to initiate automated parallel evaluation and grading.

Frequently Asked Questions about eval-harness

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

FAQPage Schema
How do I compare two code or prompt variants with automated parallel testing?▼

You can compare code, LLM prompts, CLI commands, or custom workflows by providing the TASK, VARIANT_A, VARIANT_B, INPUTS, and Evals fields to initiate automated parallel evaluation and grading.

What is parallel variant evaluation and how does it work?▼

Parallel variant evaluation uses two subagents to execute different options simultaneously with identical inputs, followed by a single model-based grading pass that produces an objective, comparable assessment with per-criterion verdicts.

Can I use this automated grading harness for LLM prompts and CLI commands?▼

Yes, the harness supports variant types including code, LLM, command, and custom workflows, using a unified input specification to ensure identical inputs across both variants for fair, apples-to-apples comparison.

What is the best way to run an apples-to-apples comparison between two implementations?▼

The best way is using a structured harness that anonymizes variants for fair judging, runs them in parallel with identical inputs, and applies a model grader to evaluate observable outputs across defined criteria.

Do I need to provide specific inputs to start automated variant comparison?▼

Yes, you must provide the TASK, VARIANT_A, VARIANT_B, INPUTS, and Evals fields to initiate the automated parallel evaluation and grading process for accurate variant comparison.