What kind of deviations does the skill detect?

It identifies critical routing violations (like bypassing required skills), cross-domain task mixing, skipped workflow steps, and suboptimal tool usage patterns.

Does Orchestration QA block my workflow execution?

No, it follows an 'observe and validate' philosophy. It identifies issues and reports them transparently through alerts and warnings but does not block the execution of your tasks.

Can I use this for any Claude Code project?

While designed for the Task Orchestrator framework, its patterns for validating skills and subagent adherence are valuable for any developer managing complex, multi-step AI workflows.

How does this skill help manage token costs?

It provides interactive configuration so you only enable the analyses you need, and it includes specific token optimization checks to identify verbose or redundant agent behaviors.

Orchestration QA

Name: Orchestration QA
Author: Angriff36

byAngriff36

Productivity & Workflow

Validates orchestration workflows and agent patterns to ensure quality, token efficiency, and architectural consistency.

About

Orchestration QA is a specialized quality assurance skill designed for complex multi-agent workflows within the Task Orchestrator ecosystem. It monitors how Claude Skills and Subagents interact, ensuring they adhere to documented patterns while identifying deviations with tiered severity levels (ALERT, WARN, INFO). By providing interactive configuration, pre-execution context capture, and post-execution efficiency analysis, it helps developers optimize token usage, improve execution graphs, and maintain high standards across automated task pipelines without blocking the development process.

Key Features

Interactive configuration to enable specific analysis categories for token efficiency
Post-execution workflow adherence validation and output quality analysis
0 GitHub stars
Pre-execution context capture and checkpointing for accurate comparison
Efficiency audits for token optimization and tool selection patterns
Automated deviation reporting with structured severity levels and recommendations

Use Cases

Validating that complex architectural plans follow established domain boundaries before execution
Auditing multi-agent token usage to reduce operational costs in large-scale coding tasks
Identifying missed parallelization opportunities in task dependency graphs for faster execution

About

Key Features

Interactive configuration to enable specific analysis categories for token efficiency
Post-execution workflow adherence validation and output quality analysis
0 GitHub stars
Pre-execution context capture and checkpointing for accurate comparison
Efficiency audits for token optimization and tool selection patterns
Automated deviation reporting with structured severity levels and recommendations

Use Cases

Validating that complex architectural plans follow established domain boundaries before execution
Auditing multi-agent token usage to reduce operational costs in large-scale coding tasks
Identifying missed parallelization opportunities in task dependency graphs for faster execution