How does this skill improve agent completion rates?

By providing standardized patterns for tool definitions and observation formats, it reduces model confusion and ensures the agent receives clear, actionable feedback after every step.

What is an agent harness?

An agent harness refers to the structural framework—including tools, observations, and logic—that surrounds an LLM to enable it to perform actions reliably and efficiently within a specific environment.

Can I use this for complex multi-tool workflows?

Yes, it specifically addresses tool granularity and context management, helping you balance micro and macro tools for complex, long-running tasks.

Does it support different architectural patterns?

Absolutely; it provides specific guidance for ReAct patterns for exploration, function calling for structured workflows, and hybrid models for optimal performance.

Agent Harness Construction

Name: Agent Harness Construction
Author: Infopibe

byInfopibe

•

Data Science & ML

Optimizes AI agent architectures by refining action spaces, tool definitions, and observation formats for higher task completion rates.

This skill provides professional guidance for building robust AI agent frameworks, focusing on the critical interface between the Large Language Model and its operational environment. It establishes best practices for designing deterministic tool schemas, managing token budgets, and implementing sophisticated error recovery contracts. By following these architectural patterns, developers can transition from fragile prompting to reliable agentic workflows using ReAct, function calling, or hybrid execution models, ensuring the agent remains focused and recovers gracefully from execution errors.

Key Features

01Architectural guidance for ReAct and hybrid execution patterns

02Advanced context budget and token management strategies

03Defined error recovery contracts with root cause analysis

041 GitHub stars

05Structured observation formats for consistent model feedback

06Standardized tool and action space design patterns

Use Cases

01Optimizing an existing agent to reduce token usage and improve success rates

02Designing a custom AI coding assistant with specialized toolsets

03Building resilient multi-step workflows that recover from API failures

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add infopibe/everything-claude-code agent-harness-construction

For use in Claude.ai and ChatGPT

Key Features

01Architectural guidance for ReAct and hybrid execution patterns

02Advanced context budget and token management strategies

03Defined error recovery contracts with root cause analysis

041 GitHub stars

05Structured observation formats for consistent model feedback

06Standardized tool and action space design patterns

Use Cases

01Optimizing an existing agent to reduce token usage and improve success rates

02Designing a custom AI coding assistant with specialized toolsets

03Building resilient multi-step workflows that recover from API failures

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add infopibe/everything-claude-code agent-harness-construction

For use in Claude.ai and ChatGPT