Agent Workflow Safety Engine

The problem

Agentic systems often suffer from silent failures, hallucinated success states, and unsafe tool execution. Developers struggle to build reliable workflows that handle edge cases, verify evidence, and maintain strict authorization boundaries without human babysitting.

What it does

• Generates structured task definitions with explicit objectives, dependencies, and acceptance criteria.
• Performs risk classification and permission gating to identify high-impact or destructive actions before they execute.
• Builds step-by-step execution plans featuring mandatory evidence checks and multi-step checkpoints.
• Designs failure recovery paths, retry strategies, and idempotency logic for distributed agent environments.
• Audits existing agent workflows for circular reasoning, security gaps, and weak handoff points.

Why this beats prompting it yourself

Simple prompts fail to enforce the verification of tool outputs, leading to "false positives" where an agent claims success without proof. This skill implements a rigorous engineering lifecycle (Define, Plan, Authorize, Execute, Verify) that treats agent actions like mission-critical software deployments.

Use cases

• Architecting multi-agent systems that require formal handoffs and validation gates.
• Hardening agents that interact with production APIs, databases, or financial systems.
• Conducting post-execution audits to verify if an agent actually met business requirements.
• Building safe human-in-the-loop workflows for high-risk autonomous tasks.

Known limitations

Does not provide the runtime environment or specific API integrations. Requires the user to supply tool definitions and execution logs for full reviews.