What problem does it solve?
Non-trivial development decisions often contain unstated assumptions, edge cases, and hidden coupling that go undetected due to accumulated context turning overconfidence into perceived correctness. These flaws lead to costly production bugs, security vulnerabilities, and irreversible errors that are far more expensive to fix after deployment than during development.
Core Features & Use Cases
- Adversarial Fresh-Context Review: Spawns an unbiased, issue-focused reviewer to disprove your non-trivial decisions (architectural choices, complex code changes, security-sensitive logic, irreversible operations like data migrations or public API updates) before they are finalized, catching flaws that accumulated context would hide.
- Bounded Review Loop: Enforces a maximum 3-cycle review process with clear stop conditions (trivial findings, user override, cycle limit) to prevent endless rework while ensuring thorough scrutiny.
- Optional Cross-Model Escalation: Offers multi-model review via external CLIs or the consensus skill for high-stakes artifacts, catching blind spots shared by a single model, with strict safety guardrails for external tool execution.
- Use Case Example: When working in an unfamiliar codebase to implement a new payment processing flow, use this skill to run an adversarial review of your logic before committing, catching edge cases around failed transactions that would lead to revenue loss and customer frustration.
Quick Start
Invoke the doubt-driven-development skill to perform an adversarial review of your proposed payment processing flow implementation before merging it to the main branch.