harness-selection

Decides whether to adopt an agent framework or build the harness for agent runtimes.

Updated Aug 2, 2026
One-click install
npx skills add https://github.com/dperussina/function2agent --skill harness-selection-dperussina
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: harness-selection
Source: https://github.com/dperussina/function2agent/tree/main/.cursor/skills/harness-selection
Command: npx skills add https://github.com/dperussina/function2agent --skill harness-selection-dperussina

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Choosing between adopting an agent framework (LangGraph, CrewAI, AutoGen, Claude Agent SDK, etc.) and building your own harness is a high-stakes architectural decision with churn, licensing, and lock-in risks. This Skill provides a pre-researched decision framework so you do not repeat that analysis from scratch. ## Core Features & Use Cases - Dependency Test: A single rule for any dependency — if it sees prompts and tokens, own it; if not, adopt it as ordinary infrastructure. - Build/Adopt Matrix by Layer: Concrete calls for HTTP transport, message abstraction, agent loop, harness features, sandboxing, durable execution, and tracing. - Churn Evidence & Anti-Recommendations: Measured evidence of framework churn (AutoGen and Semantic Kernel in maintenance mode, pre-1.0 SDKs) plus flat anti-recommendations. - Use Case: When a proposal suggests adding LangGraph or the OpenAI Agents SDK to your agent loop, apply this Skill to evaluate whether the dependency belongs in the model-facing path or the execution path. ## Quick Start Ask the agent to evaluate whether we should adopt LangGraph for our agent orchestration using the harness-selection criteria.

Frequently Asked Questions about harness-selection

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

FAQPage Schema
Should I use LangGraph or build my own agent loop?▼

Build the agent loop — it is genuinely 50–150 lines, and every framework's loop is a thin wrapper over the same logic plus opinions you did not choose. Adopt only thin substrates like vendor HTTP SDKs and durable execution behind owned interfaces.

How do I decide whether to adopt an agent framework dependency?▼

Apply the dependency test: if the dependency sees prompts and tokens, it will churn with model APIs and you should own that layer. If it sits behind the loop without touching prompts, like Temporal or sandboxing, adopt it as ordinary infrastructure.

Is AutoGen or Semantic Kernel still maintained?▼

No. Both AutoGen and Semantic Kernel are in maintenance mode; AutoGen is explicitly community-managed with no new features. Do not start anything new on either — Microsoft Agent Framework is the successor, mainly for .NET shops accepting Azure lock-in.

Can I use the Claude Agent SDK in a commercial product?▼

The SDK wrapper source is MIT-licensed, but it bundles the Claude Code CLI, which is proprietary under Anthropic's Commercial Terms. Use it inside your runtime with operator-provided entitlements, but never vendor it into a generated artifact — declare it as a peer dependency instead.

When should I adopt durable execution like Temporal for agents?▼

Adopt durable execution only when a declared durability constraint demands it — never build it yourself. Four independent teams (Pydantic AI, LlamaIndex, Mastra, Microsoft Agent Framework) integrated existing durable execution rather than building their own.

What are the risks of depending on pre-1.0 agent frameworks?▼

Pre-1.0 frameworks churn rapidly: the two lab SDKs with the most agent traffic remained pre-1.0 after 18+ months, and frameworks like AutoGen entered maintenance mode within two years. Generated artifacts bound to them break on someone else's release schedule.