# Eval Harness

> Evaluation framework for measuring agent performance

- Skill: `besync-labs/eval-harness` (Agent Skill)
- Install (CLI): `npx skillmds@latest add besync-labs/eval-harness`
- Raw SKILL.md: https://api.skillmd.com/api/skills/besync-labs/eval-harness/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: besync-labs (https://skillmd.com/u/besync-labs)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/besync-labs/eval-harness

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# Eval Harness Skill

> **Purpose**: Measure and improve agent performance through structured evaluation

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## Overview

This skill provides a framework for evaluating agent performance across key dimensions.

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## Evaluation Dimensions

### 1. Accuracy

- Did the solution work correctly?
- Were there any bugs introduced?
- Was the approach optimal?

### 2. Efficiency

- How many iterations were needed?
- Was context used efficiently?
- Were there unnecessary steps?

### 3. Alignment

- Were operating constraints followed?
- Were user preferences respected?
- Was the solution appropriate?

### 4. Quality

- Does code meet standards?
- Is it well-tested?
- Is it maintainable?

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## Evaluation Metrics

| Metric                  | Target |
| :---------------------- | :----- |
| First-time success rate | >80%   |
| Iterations to solution  | <3     |
| Test coverage           | >80%   |
| Build success           | 100%   |

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## Report Format

```markdown
# Evaluation Report

## Session: [ID]

## Task: [Description]

### Metrics

| Dimension  | Score | Notes               |
| :--------- | :---- | :------------------ |
| Accuracy   | 9/10  | Minor fix needed    |
| Efficiency | 8/10  | 2 iterations        |
| Alignment  | 10/10 | All constraints met |
| Quality    | 9/10  | Good coverage       |

### Overall: 36/40 (90%)

### Learnings

- [What went well]
- [What could improve]
```

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## Integration

- Run at session end for learning
- Use for continuous improvement