What problem does it solve? Long working sessions quietly turn assumptions into facts, and confident answers are not always correct ones. This Skill catches wrong directions early by forcing every non-trivial decision through an adversarial fresh-context review while course-correction is still cheap. ## Core Features & Use Cases - Structured Doubt Cycle: A five-step process (CLAIM, EXTRACT, DOUBT, RECONCILE, STOP) that isolates the smallest reviewable artifact and contract, then cross-examines it with an adversarial prompt. - Cross-Model Escalation: Optionally routes the artifact to external CLI reviewers (Gemini CLI, Codex CLI) via stdin with read-only sandboxing to catch single-model blind spots. - Bounded Loop with Stop Conditions: Caps review at 3 cycles, classifies findings by precedence (contract misread, actionable, trade-off, noise), and escalates unresolved artifacts to the user. - Use Case: Before committing a thread-safety change to a production caching layer, name the claim, extract the diff plus its contract, spawn an adversarial reviewer, reconcile findings, and ship only after a stop condition is met. ## Quick Start Ask the AI to apply doubt-driven development to stress-test the architectural decision or code change you are about to commit.