Why is observation design important for AI agents?

Clear tool outputs that include status, summaries, and next-action hints provide the LLM with the necessary context to decide on the next step without hallucinating state.

What is Agent Harness Construction?

It is the process of designing the interface through which an AI agent interacts with tools, formats observations, and handles errors to ensure reliable task completion.

What are the granularity rules for agent tools?

It suggests using micro-tools for high-risk operations, medium tools for common loops, and macro-tools only when reducing round-trip overhead is the primary cost concern.

Does this support ReAct or function-calling architectures?

It supports both but recommends a hybrid approach that combines ReAct-style planning with strictly typed tool execution for maximum stability.

How does this skill improve Claude's performance?

It provides strict patterns for tool granularity and observation feedback, reducing context bloat and helping the model recover from errors autonomously.

AI Agent Harness Design

Name: AI Agent Harness Design
Author: oabdelmaksoud

byoabdelmaksoud

0•

데이터 과학 및 ML

Optimizes AI agent action spaces and tool definitions to maximize completion rates and task reliability within Claude Code.

This skill provides a standardized framework for building robust AI agent harnesses, focusing on the critical interface between the language model and its operating environment. It establishes best practices for action space granularity, observation formatting, and error recovery protocols based on ECC standards. By implementing structured contracts for tool outputs and context management, it helps developers minimize hallucinations, reduce token consumption, and significantly improve the success rate of complex, multi-step agentic workflows.

주요 기능

01Context Budgeting Strategies to minimize prompt overhead and manage token limits

02Optimized Action Space Design with stable, schema-first tool definitions

03Granular Tooling Rules for micro, medium, and macro-tool selection

04Observation Formatting Standards for status, summary, and next-action tracking

05Error Recovery Contracts with root cause hints and safe retry instructions

060 GitHub stars

사용 사례

01Designing custom Claude Code skills with high reliability and low error rates

02Optimizing agentic performance for high-risk deployment and infrastructure tasks

03Refactoring complex agent toolsets to improve ReAct planning and execution

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add oabdelmaksoud/superclaw agent-harness-construction

For use in Claude.ai and ChatGPT

주요 기능

01Context Budgeting Strategies to minimize prompt overhead and manage token limits

02Optimized Action Space Design with stable, schema-first tool definitions

03Granular Tooling Rules for micro, medium, and macro-tool selection

04Observation Formatting Standards for status, summary, and next-action tracking

05Error Recovery Contracts with root cause hints and safe retry instructions

060 GitHub stars

사용 사례

01Designing custom Claude Code skills with high reliability and low error rates

02Optimizing agentic performance for high-risk deployment and infrastructure tasks

03Refactoring complex agent toolsets to improve ReAct planning and execution

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add oabdelmaksoud/superclaw agent-harness-construction

For use in Claude.ai and ChatGPT