awesome-harness-engineering
by ai-boost
Curated resources for building and testing agent harnesses and evaluation pipelines
Overview
Curates tools, patterns, and references for building AI agent harnesses and evaluation infrastructure. Organizes links across memory, MCP, permissions, observability, orchestration and benchmarking to help teams design testable agent workflows. Includes playbooks and community projects that illustrate evaluation patterns and failure-mode analysis. For example, the collection emphasizes reliable interfaces like the Model Context Protocol (MCP) and practical orchestration approaches such as the Event-Driven Agent Pattern.
The Value Proposition
Ideal For
Engineers and researchers assembling evaluation harnesses, benchmarks, and observability workflows for multi-agent systems. This toolkit is especially useful for teams building robust agent registries and collaboration patterns, including those exploring multi-agent coordination via the Agent Registry Pattern.
How It's Used
- Discovering libraries and examples for building continuous agent evaluation pipelines
- Finding observability and logging patterns for agent interaction and failure-mode analysis
- Surveying benchmarks, MCP and permission solutions when designing multi-agent testbeds