ai-ad-agents-test-orchestrator

Orchestrate static test inspections to gate AI agent deployments.

Updated Nov 8, 2025
One-click install
npx skills add https://github.com/wade56754/AI_ad_spend02 --skill ai-ad-agents-test-orchestrator
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ai-ad-agents-test-orchestrator
Source: https://github.com/wade56754/AI_ad_spend02/tree/main/.claude/skills/ai-ad-agents-test-orchestrator
Command: npx skills add https://github.com/wade56754/AI_ad_spend02 --skill ai-ad-agents-test-orchestrator

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solves?

Ensuring the quality and stability of AI agents after code changes requires continuous testing, but full test runs can be time-consuming. This Skill orchestrates static test patrols for AI agents, automatically mapping code changes to relevant tests, executing them one by one, and providing a quality gate verdict for deployment.

Core Features & Use Cases

  • Change-Driven Test Selection: Automatically identifies and runs only tests relevant to recent code changes in agents/ or skills/ directories.
  • Static Test Execution Orchestration: Calls ai-ad-agents-test-runner to perform static analysis-based tests, tracking PASS/FAIL/UNCERTAIN outcomes.
  • Quality Gate Verdict: Provides a clear "BLOCK", "ALLOW", or "WARN" verdict based on test results, acting as a pre-CI/CD quality gate.
  • Use Case: After modifying an AI agent's core logic, use this Skill to automatically run a targeted test patrol. It will identify affected tests, execute them statically, and tell you if your changes are safe to proceed to full CI/CD, accelerating your development and ensuring quality.

Quick Start

Use ai-ad-agents-test-orchestrator with "auto" scope for changed files 'agents/agent_core/fe_agent.py' and 'agents/tools/fs_tool.py'.

Frequently Asked Questions about ai-ad-agents-test-orchestrator

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

FAQPage Schema
How do I automatically run tests after AI agent code changes?

This Skill orchestrates static test execution by mapping changed files in your agents/ codebase to relevant tests, then invoking ai-ad-agents-test-runner to execute them sequentially without pytest, delivering a BLOCK/ALLOW/WARN quality gate verdict for deployment.

Can I use automated testing to gate AI agent deployments before CI/CD?

Yes. This Skill acts as a pre-deployment quality gate, analyzing code changes across agent_core, skills, and tools directories, selecting only affected tests, and providing a clear pass/fail verdict to prevent unsafe deployments.

What's the best way to run targeted regression tests for AI agents?

Change-driven test selection automatically identifies tests relevant to your modifications in agents/ or skills/, executes them through static analysis orchestration, and reports coverage assessment and test outcomes without full test-suite overhead.

How does static test orchestration work for AI agent quality assurance?

The Skill implements a five-stage read-only workflow: ANALYZE-CHANGES identifies modified files, DISCOVERY maps them to tests, SELECT-TESTS filters by scope, RUN-LOOP executes tests individually, and SUMMARY delivers verdicts—all without writing files or executing pytest directly.

Can I validate AI agent changes locally before submitting pull requests?

Yes. The Skill supports quick local validation by accepting changed_files input and optional test_scope parameters, running targeted static-analysis tests immediately, and blocking unsafe changes before PR submission.

What are the limitations of static test orchestration for AI agents?

The Skill performs static analysis without executing pytest or writing files, so it cannot verify runtime behavior or side effects. Full CI/CD testing remains necessary for comprehensive validation before production deployment.