What it does

The Agent Workflow Controller is a sophisticated architectural skill designed for developers and AI orchestrators who need to manage complex, multi-step, or multi-agent tasks. It acts as the "operating system" for your agent's logic, transforming vague requests into structured execution plans with defined phases, roles, and boundaries.

Problem it solves

Standard LLM prompts often struggle with "agentic drift," where agents duplicate work, provide unverifiable outputs, or fail during handoffs. This skill prevents collaboration breakdown by enforcing ownership, explicit exit gates, and evidence-based verification. It moves beyond simple prompting by introducing professional workflow engineering—ensuring your agents act with the precision of a coordinated team rather than a single black box.

Supported Workflows

• Discovery-Execute-Verify: For tasks where the state is unknown.
• Approval-Gated: For high-risk, destructive, or financial operations.
• Parallel Slice: For independent sub-tasks requiring disjoint ownership.
• Failure-Repair Loop: For systematic debugging when a process fails.

The Output

The skill produces a comprehensive Workflow Plan. This includes a mission statement, complexity classification, a role/purpose matrix, ownership maps for files and decisions, and concrete verification plans that tie every claim to specific evidence (logs, diffs, or citations).