testpulse-v13-review

To identify high-risk findings in PRD diffs and agent specs, apply a findings-first review lens to surface bugs, contract drift, missing tests, and security issues. This process ranks issues by severity and checks cross-surface consistency between Python models, API surfaces, MCP, and frontend types.

Cross-surface drift detection in code reviews is the process of checking consistency between Python models, API surfaces, MCP, and frontend types. It articulates actionable remediation notes for validation gaps and contract mismatches found across different layers of an application.

Review implementation diffs for missing tests and security issues by enforcing a structured, findings-first audit that focuses on bugs and validation gaps. This generates a severity-ordered report with explicit residual risk notes to guide safe decision-making without proposing implementations.

Yes, you can use an AI-driven review lens to evaluate PRD revisions for contract drift and bugs. It analyzes plan revisions and diffs to return a severity-ranked report, ensuring that high-risk issues are identified before implementation begins.

No, this review approach does not propose code implementations for the issues found. It strictly enforces a findings-first review structure that highlights severity-ranked issues, cross-surface drift, and explicit residual risk notes to guide independent remediation.

The best way to audit TestPulse v1.3 plans for validation gaps is to apply a findings-first AI review lens to the diffs and plans. This surfaces high-risk issues across Python models and frontend types, returning a structured report with severity ordering and residual risk notes.