prompt
FreeDesign real-world evaluations for AI agents
FreeFree tier
Inputs: textOutputs: text
About prompt
Agent Eval Designer is a prompt from the ai-boost/awesome-prompts repository that instructs an LLM to act as an agent evaluation architect. It provides a structured framework for designing evaluations of AI agents that measure real-world usefulness rather than toy benchmarks. The prompt covers defining the task, environment, measuring noise, scoring beyond success rate (e.g., cost, latency, intervention rate), building failure-driven evaluation sets, and more. It draws inspiration from Anthropic's work on evaluating AI agents.
Key Features
Provides a structured framework for evaluating AI agents
Separates model capability from harness quality, tool reliability, environment noise, and task selection bias
Includes scoring metrics beyond success rate: completion rate, cost, latency, intervention rate, reversibility/damage risk, trajectory quality
Emphasizes failure-driven evaluation sets including interruption, ambiguity, rollback, and deceptive-context cases
Advocates for executable tasks over subjective judgments
Recommends measuring noise sources like flaky tests, network variance, tool instability
Supports reporting confidence intervals and tracking unsafe vs. safe success
Covers environment specification with tools, permissions, datasets, runtime limits
Pros & Cons
Pros
- Comprehensive framework that goes beyond simple success rate
- Focuses on realistic, failure-driven testing
- Separates noise from actual model performance
- Includes safety and cost metrics
- Open source and freely available on GitHub
Cons
- Requires technical understanding of agent evaluation
- No built-in implementation or execution environment provided
- May need custom adaptation for specific agent systems
- No official support or maintenance beyond the repository
Best For
Evaluating AI agents in real-world scenariosBenchmarking whole agent systems rather than base modelsAssessing agent reliability and safety across repeated runsDesigning evaluation suites for agent development teams
FAQ
What is the Agent Eval Designer prompt?
It is a prompt from the ai-boost/awesome-prompts repository that instructs an LLM to act as an agent evaluation architect, designing evaluations for AI agents based on principles from Anthropic's research.
How do I use this prompt?
Copy the prompt text from the GitHub file and use it with an LLM (e.g., ChatGPT, Claude) to generate a custom evaluation plan for an AI agent.
What metrics does the prompt recommend?
It recommends primary metrics (completion rate), secondary metrics (cost, latency, intervention rate), safety metrics, and trajectory quality, along with noise measurement.
Is this prompt free?
Yes, the prompt is open source and available for free on GitHub as part of the awesome-prompts repository.