AI workflow instructions often fail not because the model is wrong, but because the instructions are incomplete, vague, or structurally unsound. Workflow Doctor is a diagnostic tool inside TryPromptFlow that checks your instructions across five dimensions: completeness, specificity, executability, constraint fidelity, and test coverage alignment. Each stage must pass before the next runs. It returns a corrected artifact, paste-ready operator rules, and a release confidence note — a go/no-go signal based on deterministic rules, not AI opinion. Workflow Doctor does not run live AI agents. It diagnoses instructions before they are used.
For pre-launch diagnosis of bot-driven and AI-executed workflows, Agentic Workflow Doctor reviews the full workflow design — approval gates, action boundaries, recovery risks, and runtime controls.
Workflow Doctor runs a five-stage diagnostic on your AI workflow instructions — checking completeness, specificity, executability, constraint fidelity, and test coverage alignment. Each stage must pass before the next runs. It returns a corrected artifact, paste-ready operator rules, and a release confidence note.
A release confidence note is a deterministic, rules-based go/no-go signal — not an AI opinion. It tells you whether the repaired workflow instruction is ready for controlled use, needs human review, or should not be released yet.
No. Workflow Doctor diagnoses and repairs workflow instructions. It does not run live AI agents, execute workflows, or manage any running AI system. It operates before deployment, not during it.
Workflow Doctor works on prompts, SOPs, checklists, and workflow instruction sets used to guide AI systems. It is not specific to any one AI model or platform.
Asking an AI to rewrite a prompt produces a different prompt — it does not diagnose why the original failed. Workflow Doctor identifies specific structural failure points and produces a corrected artifact with explicit requirements and operator acceptance tests.