skills.rest
thatditsyboy
thatditsyboyCOMMUNITY
Explore all skills by this author →
GitHub

hive-test

Execute, analyze, and resume iterative AI agent testing sessions from checkpoints.

Updated Mar 4, 2026
Search Tags:#debugging#ai#iteration#recovery#agent testing
One-click install
npx skills add https://github.com/thatditsyboy/aden-pricing-tracker --skill hive-test-thatditsyboy
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: hive-test
Source: https://github.com/thatditsyboy/aden-pricing-tracker/tree/main/.claude/skills/hive-test
Command: npx skills add https://github.com/thatditsyboy/aden-pricing-tracker --skill hive-test-thatditsyboy

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the challenges of iterative testing for AI agents by enabling session recovery and efficient iteration, making debugging and verification more efficient.

Core Features & Use Cases

  • Iterative Agent Testing: Execute tests, analyze failures, fix issues, and resume from checkpoints without restarting.
  • Session Recovery: Preserve runtime data and enable recovery from the last clean checkpoint.
  • Use Case: When building a new agent or fixing an existing one, use this Skill to perform comprehensive testing with ease.

Quick Start

Use the hive-test skill to test an agent by executing it with the command 'uv run hive test --goal my_goal --agent agent_path'.

Frequently Asked Questions about hive-test

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

FAQPage Schema
How do I resume AI agent testing from a checkpoint after a failure?▼

Session recovery for AI agent testing allows you to resume execution from the last clean checkpoint. This preserves runtime data, enabling iterative debugging without restarting the entire testing session.

What is the best way to debug an AI agent iteratively without losing runtime data?▼

Iterative agent testing frameworks support executing tests, analyzing failures, and fixing issues while preserving runtime data. You can resume executions from checkpoints, making debugging efficient and preventing data loss.

How do I generate synthetic test inputs for AI agent testing?▼

Iterative testing frameworks provide capabilities to generate synthetic test inputs for AI agents. This allows you to run comprehensive executions and analyze agent behavior against varied simulated data.

Can I run AI agent testing and analysis directly from the command line?▼

Yes, you can execute agent testing and analysis directly via command line. Use the command 'uv run hive test --goal my_goal --agent agent_path' to start testing your AI agent packages.

What dependencies do I need to run iterative tests on my AI agents?▼

To run iterative tests on AI agents, you need valid agent packages and the necessary credentials. These components are required by the framework to execute tests and manage session recovery.

Related Skills

Explore More Software Engineering Skills→
nesihaver-ILnesihaver-IL

azure-ai-foundry

Build and orchestrate AI agents on Azure AI Foundry with Python SDKs.

Community
Advanced
nk10nikhilnk10nikhil

hive-test

Run iterative agent tests with checkpoint resume and failure analysis.

Community
Advanced
adamatdevopsadamatdevops
1

error-analysis

Analyze LLM pipeline traces to prioritize failure modes by root cause.

Community
Intermediate
maslennikov-igmaslennikov-ig
243

save-session-context

Save current health orchestrator workflow state to a context file.

Community
Basic