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tool-program-harness

Test AI tool programs across deterministic, live-model, and ACP transport modes.

Updated May 6, 2026
Search Tags:#automation#testing#validation#rust#chaos-engineering#tool-programs
One-click install
npx skills add https://github.com/dbowm91/codegg --skill tool-program-harness
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tool-program-harness
Source: https://github.com/dbowm91/codegg/tree/main/.opencode/skills/tool-program-harness
Command: npx skills add https://github.com/dbowm91/codegg --skill tool-program-harness

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill addresses the difficulty of ensuring that AI-generated tool programs are reliable, performant, and resilient against runtime failures or unexpected model behavior.

Core Features & Use Cases

  • Multi-Mode Validation: Test tool programs across deterministic, live-model, and ACP transport environments.
  • Fault Injection: Simulate real-world chaos, including broker failures, budget exhaustion, and worker panics to ensure robust error handling.
  • Resource Convergence: Monitor and verify that programs adhere to strict resource bounds, preventing memory leaks or runaway processes.

Quick Start

Execute the tool program harness in native mode to validate your current tool program implementation against the defined scenario suite.

Frequently Asked Questions about tool-program-harness

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I validate AI tool programs against unexpected model behavior?▼

You can validate AI tool programs by running them through a testing harness that supports scenario-based testing across deterministic, live-model, and ACP transport environments to ensure reliability.

How does fault injection work for testing AI agent resilience?▼

Fault injection simulates real-world chaos scenarios like broker failures, budget exhaustion, and worker panics within your test suite to verify robust error handling in AI tool programs under stress.

Do I need Python and Rust toolchains to run AI tool program validation?▼

Yes, you need both Python 3 and Rust toolchains installed to execute the integrated testing harness and run the validation scenario suite for AI agents.

What is the best way to monitor resource convergence in AI agents?▼

The best way to monitor resource convergence is using a testing framework that verifies programs adhere to strict resource bounds, preventing memory leaks or runaway processes during execution.

Can I use scenario-based testing for debugging AI tool programs in production?▼

Yes, you can use scenario-based testing to debug production-grade AI agents by executing the native test harness to evaluate your tool program implementation against a defined scenario suite.

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