Bot-driven and AI-executed workflows fail when assumptions misalign with reality. Find approval gaps, broken action boundaries, state failures, and missing recoveries before your agents go live.
Agentic workflows fail when the design assumptions are wrong — not always when the AI model is wrong. Missing approval gates, undefined recovery behavior, unclear action boundaries, and unsafe state assumptions create failures that surface only after the workflow runs. Agentic Workflow Doctor reviews the full workflow design before launch.
To audit your agent, provide the system prompts, tool definitions (functions/APIs the agent can call), state management approach, and a diagram or description of the workflow graph. Providing failure logs helps pinpoint missing recovery nodes.
What the system may and may not do. Are external tool usage scopes explicitly restricted and safe?
How context is tracked and passed between steps. Are state assumptions safe for long-running workflows?
What happens when a step or tool fails? Are fallback behaviors and retry loops structurally defined?
Steps requiring human sign-off. Where must a person stay in the loop to prevent downstream consequences?
Agentic Workflow Doctor flags structural control risks before they hit production.
Agent: Support Bot Instructions: Answer the customer, look up their order, and issue a refund using issue_refund(order_id) if it seems needed.
Findings: — No monetary limit on issue_refund. — No identity validation (caller vs. order_id owner). — No recovery path if issue_refund API times out. — No human approval gate for high-value decisions. Repair Targets: 1. Wrap issue_refund in a $50 hard cap. 2. Add verify_identity(user_token) before order_lookup. 3. Define timeout fallback: escalate to Human Queue. 4. Require operator_approval for refunds > $50.
TryPromptFlow works from the workflow information and evidence you provide. It does not automatically verify a fix or gate a release, and it does not continuously monitor, connect to, modify, or deploy changes to your live systems.
Agentic Workflow Doctor is a design diagnostic, not a runtime system. It does not run the workflow, deploy agents, or monitor live systems. It does not guarantee safety or compliance. Human judgment is always required before production.
Agentic Workflow Doctor is a pre-launch diagnostic tool for bot-driven and AI-executed workflows. It reviews the workflow design — approval gates, action boundaries, recovery behavior, state handling, runtime risks, and human oversight requirements — and returns a readiness scorecard, repair report, and paste-ready controls before the workflow runs.
No. Agentic Workflow Doctor diagnoses the workflow design before it is deployed. It does not run, execute, monitor, or deploy AI agents or workflows. It operates on the instructions and design, not on live systems.
Agentic Workflow Doctor checks for: approval gaps (steps requiring human sign-off with none defined), action-boundary problems (the system acting outside its intended scope), missing recovery behavior (what happens when a step fails), state-handling gaps (how the workflow tracks and passes context), runtime risks (unsafe assumptions that cause failures at execution), insufficient human oversight, unclear external side effects, and missing success criteria.
Agentic Workflow Doctor returns: a decision snapshot (executive readiness verdict), a release-readiness scorecard, a repair report with prioritized findings, a repaired workflow, defined approval gates, a recovery plan, a state plan, runtime tests, an implementation checklist, paste-ready control clauses, and prompt-ready improvements for the workflow instructions.
Yes. Agentic Workflow Doctor supports human review — it does not replace it. It does not guarantee safety, compliance, or production readiness. A human must review the repair report, apply judgment about the deployment context, and make the final decision before the workflow runs.
Agentic Workflow Doctor reviews the full workflow design — approval structure, recovery paths, action boundaries, runtime risks, and controls — before launch. PromptFlow Creator works at the prompt level: it improves and repairs the individual instructions given to an AI tool. Agentic Workflow Doctor operates on the workflow as a system; PromptFlow Creator operates on individual prompts within it.