# Adversarial Code Review For Committed Diffs

> Systematic process for reviewing already-committed code changes to catch type inconsistencies, edge cases, and docstring gaps

- Skill: `vamseeachanta/adversarial-code-review-for-committed-diffs` (Agent Skill)
- Install (CLI): `npx skillmds@latest add vamseeachanta/adversarial-code-review-for-committed-diffs`
- Raw SKILL.md: https://api.skillmd.com/api/skills/vamseeachanta/adversarial-code-review-for-committed-diffs/raw
- Safety review: PASS (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: vamseeachanta (https://skillmd.com/u/vamseeachanta)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/vamseeachanta/adversarial-code-review-for-committed-diffs

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# Adversarial Code Review for Committed Diffs

When code is already pushed and tests pass, perform targeted adversarial review: (1) Identify design choices (quantile indexing, boundary conditions, return types), (2) Check for type annotation inconsistencies (e.g., `int` returned in `dict[str, float]`), (3) Test edge cases (empty sets, zero-duration phases, n=2 quantiles), (4) Verify docstring completeness against implementation. Route minor findings to focused GitHub issues rather than requiring a fix round if core logic is sound.