Does it support safe deployment?

Yes, it includes guidelines for staged rollouts (Alpha/Beta/Canary) and defines specific rollback triggers to protect production environments from quality regressions.

What metrics are used to measure agent success?

The skill focuses on task success rates, tool call efficiency, response latency, token consumption, and user satisfaction indicators like correction frequency.

When should I use the agent-orchestration-improve-agent skill?

Use this skill when you have an existing agent that needs performance tuning, reliability improvements, or systematic evaluation against specific metrics rather than building a new one from scratch.

How does this skill help with prompt engineering?

It provides structured workflows for Chain-of-Thought enhancement, curated few-shot examples, and role definition refinement to improve reasoning and output quality.

Agent Performance Optimizer

Name: Agent Performance Optimizer
Author: sickn33

bysickn33

•

31,722

•

データサイエンスとML

Optimizes AI agent performance through systematic analysis, structured prompt engineering, and rigorous A/B testing workflows.

The Agent Performance Optimizer is a comprehensive framework designed to elevate existing AI agents from basic prototypes to production-ready tools. It guides developers through a data-driven lifecycle of improvement, starting with baseline metric collection and failure mode analysis. The skill facilitates advanced prompt engineering techniques—such as Chain-of-Thought optimization and few-shot curation—and provides a structured methodology for A/B testing and staged rollouts. By focusing on measurable goals and safety-first deployment, it ensures that every iteration results in tangible gains in reliability, accuracy, and cost-efficiency.

主な機能

01Baseline performance metric collection and failure mode classification

02Staged rollout strategies with defined rollback triggers

03Advanced prompt engineering including CoT and few-shot optimization

04Constitutional AI integration for automated self-correction

0531,722 GitHub stars

06Automated A/B testing framework for comparing agent versions

ユースケース

01Reducing hallucination rates and improving tool usage efficiency

02Fixing recurring failure patterns in production customer support agents

03Benchmarking prompt iterations against established performance baselines

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add sickn33/antigravity-awesome-skills agent-orchestration-improve-agent

For use in Claude.ai and ChatGPT

主な機能

01Baseline performance metric collection and failure mode classification

02Staged rollout strategies with defined rollback triggers

03Advanced prompt engineering including CoT and few-shot optimization

04Constitutional AI integration for automated self-correction

0531,722 GitHub stars

06Automated A/B testing framework for comparing agent versions

ユースケース

01Reducing hallucination rates and improving tool usage efficiency

02Fixing recurring failure patterns in production customer support agents

03Benchmarking prompt iterations against established performance baselines

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add sickn33/antigravity-awesome-skills agent-orchestration-improve-agent

For use in Claude.ai and ChatGPT