prompt
FreeBest practices for building, debugging, and evaluating agentic harnesses
FreeFree tier
About prompt
A comprehensive, provider-neutral prompt/skill file for designing, auditing, refactoring, and explaining agentic harnesses. Covers agent loops, tool design, permissions, system prompts, planning, goals, context compaction, memory, skills, MCP/external connectors, observability, evals, prompt caching, agent-legible environments, feedback loops, and safety. Intended for use with OpenAI, Anthropic, and OpenAI-compatible APIs. Part of the ai-boost/awesome-prompts open-source collection.
Key Features
Provider-neutral agent architecture (OpenAI, Anthropic, OpenAI-compatible APIs)
Covers agent loops, tool design, permissions, and guardrails
Includes planning modes, goal tracking, and long-running task behavior
Context compaction, memory, retrieval, and prompt hierarchies
MCP/external connectors, observability, evals, and prompt caching
Safety, approval flows, sandboxing, and agent-legible environments
Scoped to multiple domains: coding, research, finance, legal, support, operations, sales, healthcare, education, data analysis, procurement, workflow automation
Pros & Cons
Pros
- Comprehensive coverage of agent architecture best practices
- Provider-neutral and API-agnostic
- Includes safety, observability, and evaluation considerations
- Applicable across many domains and use cases
- Open-source and freely available
Cons
- Static text file – no interactive or executable components
- Requires manual implementation of concepts
- Not a standalone tool or framework
Best For
Building an agent, agentic workflow, AI worker, or autonomous assistantCreating domain-specific MVP agent designs or implementation blueprintsAuditing an existing agent for reliability, cost, safety, latency, or observabilityDesigning tools, permissions, guardrails, and approval flowsAdding memory, retrieval, skills, or external connectors to agentsDeveloping system prompts or developer instructions for domain-specific agents
FAQ
What is an agent harness?
An agent harness is the control plane around a model. The model proposes actions; the harness validates, authorizes, executes, records, summarizes, and returns observations. The loop is kept simple while the runtime is made rigorous.
Which APIs does this best practices guide support?
It covers provider-neutral agent architecture for OpenAI, Anthropic, and OpenAI-compatible APIs.
When should I use this skill?
Use it when building, improving, debugging, or evaluating an agentic harness. It is intended for prompts involving agent design, MVP blueprints, auditing, refactoring, or explaining autonomous assistants.