dk-loop-audit

Autonomous loop readiness measures whether an AI agent can independently close the problem-solving loop from symptom discovery to verified fix without human input. It evaluates tooling, documentation, and workflow completeness across development environments.

To audit AI tooling readiness, provide the target area or workflow to evaluate. The assessment enforces explicit criteria across discovery, diagnosis, hypothesis, fix, verify, and documentation stages to identify gaps in autonomous problem-solving capabilities.

A gap analysis is needed when evaluating debugging readiness in a new feature area or a workflow requiring minimal human intervention. It produces actionable gap-focused reports with ratings to guide improvements in documentation, diagnostics, and workflows.

Yes, structured templates for loop-audit reports are enforced during evaluation. These templates ensure explicit evaluation criteria are met and actionable gap reporting is generated to assess autonomous problem-solving capabilities across all stages.

The assessment evaluates six stages: discovery, diagnosis, hypothesis generation, fix implementation, verification, and documentation. Each stage is assessed against explicit criteria to determine if an AI agent can autonomously close the problem-solving loop.

No dependencies or external components are required to run the autonomous loop readiness evaluation. The assessment operates independently to evaluate AI agent capabilities and generate structured gap-focused reports with actionable improvement recommendations.