# ai-boost/awesome-harness-engineering

Awesome list for AI agent harness engineering: tools, patterns, evals, memory, MCP, permissions, observability, and orchestration.

Repository: https://github.com/ai-boost/awesome-harness-engineering
Canonical: https://ross.abutalabs.com/products/ai-boost-awesome-harness-engineering
Homepage: https://github.com/ai-boost/awesome-harness-engineering
Language: Python
License: NOASSERTION
License Family: other
Topics: agent-harness, agent-memory, agent-orchestration, ai-agents, awesome-list, context-engineering, harness-engineering, mcp, ai-agent-harness
Last push: 2026-08-26T06:58:41+00:00

## Health v2 (maintenance only)
Score: 59/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 35, longevity 11
- inputs: {"age_days": 157, "days_push": 7, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, young, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3817, forks 454 (observed 2026-08-28T04:08:20.815874+00:00)

## What it is
A curated awesome list of resources, patterns, and templates for AI agent harness engineering, covering tools, evals, memory, MCP, permissions, observability, and orchestration. It focuses on the scaffolding around AI agents rather than the models themselves.

## Use cases
- find tools for building AI agent harnesses
- learn context engineering patterns for LLM agents
- discover MCP servers and agent orchestration resources
- research agent memory and state management approaches
- find eval and verification tooling for AI agents
- learn about agent permissions and sandboxing

## When to choose
- you are building or hardening AI agent systems and want curated references
- you want a survey of harness engineering tools, patterns, and templates
- you need starting points for agent memory, evals, or orchestration

## When to avoid
- you need runnable software rather than a curated link list
- you want model training or fine-tuning resources
- you need a specific framework with support guarantees

## Facets
- artifact type: learning-resource
- maturity: active
- function: agent-framework, mcp, developer-tools, documentation
- domain: large-language-models, developer-tools, awesome-lists
- platform: cross-platform
- tags: awesome-list, harness-engineering, context-engineering, agent-orchestration, agent-memory, evals, observability, ai-agents

## Member repositories
- ai-boost/awesome-harness-engineering (main) score 59

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:20.815874+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:26:30.001693+00:00, confidence not recorded.
  - readme: https://github.com/ai-boost/awesome-harness-engineering (fetched 2026-08-28T04:08:20.815874+00:00, sha 91f761a9828f)
  - homepage: https://github.com/ai-boost/awesome-harness-engineering (fetched 2026-08-29T09:21:24.906191+00:00, sha f824e7fb1071)
- Data as of 2026-08-30T08:39:29.467469+00:00.